GIS interference source positioning method based on VFTO analysis, electronic equipment and storage medium

Abstract

The invention discloses a VFTO analysis-based interference source positioning method for a GIS (Geographic Information System), electronic equipment and a storage medium, which are used for WAPI (Wireless Local Area Network Application Program Infrastructure) equipment of a GIS system, and the method comprises the following steps: extracting VFTO waveform data in a wireless local area network security protocol AP of the GIS system; performing noise reduction processing on the VFTO waveform data, and decomposing the VFTO waveform data after noise reduction into a plurality of intrinsic mode functions of different frequency components; performing Hilbert transform on each intrinsic mode function to construct a Hilbert spectrum; through Hilbert spectrum, an interference source is positioned based on the propagation characteristics of interference signals and the physical layout of the system. The VFTO generated by the WAPI equipment is analyzed and processed, the interference source is determined, the complex industrial environment with strong electromagnetic interference can be dealt with, and the stability and reliability of the WAPI wireless environment are ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of transient signal processing inside a GIS, and in particular relates to a method for locating interference sources based on VFTO analysis in a GIS, an electronic device and a storage medium. Background Art

[0002] Geographic Information System (GIS) is a spatial information system. Very Fast Transient Overvoltage (VFTO) may be generated due to the switching operation of the disconnector, circuit breaker and other devices in GIS or the external lightning overvoltage. Among them, the VFTO generated when operating the disconnector is the most serious. When the isolating knife starts to open at the voltage peak, since the voltage on the unloaded bus is maintained at Em, and the voltage on the power supply side still changes in a sinusoidal law, arc breakdown will occur when the rising speed of the transient overvoltage is greater than or equal to the electron avalanche critical value of SF6. At this time, the current will flow from the power supply side to the unloaded bus side through the arc, causing the voltage on the unloaded side to jump to synchronize with the voltage on the power supply side, accompanied by high-frequency oscillation, generating VFTO. Since the isolating knife has no arc extinguishing ability, the arc will continue until the high-frequency current decays, and the arc will extinguish when it cannot maintain energy to continue burning. Since the voltage on the power supply side still changes according to the sinusoidal law and the voltage on the no-load side maintains the residual voltage at the moment the arc is disconnected, when the recovery voltage between the contacts is greater than the breakdown voltage again, the contacts will be broken down again, and the cycle will repeat until the recovery voltage is no longer greater than the breakdown voltage between the contacts, the contacts are completely disconnected, and the tripping ends.

[0003] Since the bandwidth equipment in the converter station is uniformly connected using the WAPI wireless LAN, in order to cope with the complex industrial environment with strong electromagnetic interference and ensure the stability and reliability of the WAPI wireless environment, it is necessary to evaluate the impact and harm of VFTO on WAPI equipment, and thus analyze the source of interference. Summary of the invention

[0004] The purpose of the present invention is to identify the interference source, thereby avoiding strong electromagnetic interference and providing a GIS system interference source positioning method based on VFTO analysis for a WAPI wireless environment that provides a stable and reliable operating environment.

[0005] In order to achieve the above-mentioned purpose, the present invention proposes a method for locating interference sources of a GIS system based on VFTO analysis, which is used for a WAPI device of a GIS system. The method comprises: extracting VFTO waveform data in a wireless local area network security protocol AP of a GIS system; performing noise reduction processing on the VFTO waveform data; decomposing the denoised VFTO waveform data into intrinsic mode functions of several different frequency components; performing Hilbert transform on each of the intrinsic mode functions to construct a Hilbert spectrum; and locating the interference source through the Hilbert spectrum based on the propagation characteristics of the interference signal and the physical layout of the system.

[0006] In an optional implementation, the interference source is located by the Hilbert spectrum based on the propagation characteristics of the interference signal and the physical layout of the system, specifically including: performing a Hilbert transform on each of the intrinsic mode functions to extract time-frequency information, where the time-frequency information includes instantaneous frequency and instantaneous amplitude; accumulating the instantaneous frequency and instantaneous amplitude of the components of all the intrinsic mode functions to construct the Hilbert spectrum: In the formula, δ(f-ω k (t)) is the unit impulse function, |IMF k (t)| is the instantaneous amplitude.

[0007] In an optional embodiment, the interference source is located through the Hilbert spectrum based on the propagation characteristics of the interference signal and the physical layout of the system, specifically including: extracting the change law of the instantaneous frequency over time from the intrinsic mode function to obtain the main characteristic frequency component of the VFTO waveform data after noise reduction; according to the main characteristic frequency component, comparing the characteristic frequency and amplitude of each of the test points through the Hilbert spectrum to determine the area with the strongest spectral energy; based on the area with the strongest spectral energy, according to the time starting point difference of the instantaneous frequency in the Hilbert spectrum, inferring the propagation path of the VFTO waveform data at different test points to obtain the inferred distance, and the calculation formula is as follows: d=v×Δt; wherein d is the distance between the test point and the interference source, positioning is the inferred distance, v is the signal propagation speed, and Δt is the arrival time difference of the instantaneous frequency; the position of the interference source is obtained according to the inferred distance.

[0008] In an optional implementation, the interference source is located by the Hilbert spectrum based on the propagation characteristics of the interference signal and the physical layout of the system, specifically including: based on the Hilbert spectrum, comparing the time-frequency energy distribution of different test points to obtain the frequency band with the maximum instantaneous energy; obtaining the test point according to the frequency band with the maximum instantaneous energy; analyzing the attenuation law of the instantaneous energy of the characteristic frequency of the test point with distance, and establishing an energy attenuation model, wherein the calculation formula of the instantaneous energy is as follows: Where, E(d) is the instantaneous energy at the distance from the measured point to the interference source, E 0 is the optimal initial energy, α m is the optimal attenuation coefficient, and d is the estimated distance.

[0009] In an optional implementation, based on the energy attenuation model, the position of the interference source is obtained by fitting the energy distribution, specifically including: estimating the attenuation coefficient and the initial energy; solving the fitted attenuation coefficient and the initial energy according to the error function to obtain the optimal attenuation coefficient and the optimal initial energy, wherein the error function is as follows:

[0010] Based on the optimal attenuation coefficient, the optimal initial energy and the energy attenuation model, the distance from the interference source to the point to be measured is obtained, and the calculation formula is as follows: In the formula, E 0 is the optimal initial energy, E 1 is the energy of a certain point to be measured, E i is the instantaneous energy of the i-th measured point at the interference source, d i is the distance between the i-th test point and the interference source, α m is the optimal attenuation coefficient, d is the estimated distance; the position of the interference source is obtained based on the estimated distance.

[0011] In an optional embodiment, the denoised VFTO waveform data is decomposed into several intrinsic mode functions of different frequency components, specifically comprising: decomposing the denoised VFTO waveform data by an EMD algorithm to obtain a plurality of the intrinsic mode functions, and the calculation formula is as follows: Where ξ(t) is the original signal, IMF i are K intrinsic mode functions, r K It is the remainder after subtracting the IMF from the original signal.

[0012] In an optional implementation, each of the intrinsic mode functions is subjected to a Hilbert transform to extract time-frequency information, wherein the time-frequency information includes instantaneous frequency and instantaneous amplitude, specifically comprising: assuming that a component of an intrinsic mode function is IMF k (t), the result of Hilbert transform is: Where H represents the Hilbert transform operation, IMF k (t) is the kth intrinsic mode function of the signal; the instantaneous frequency and instantaneous amplitude are obtained by the Hilbert transform; wherein the calculation formula of the instantaneous frequency is as follows: Wherein, arg() represents the phase operation; the calculation formula of the instantaneous amplitude is as follows: In the formula, j is an imaginary unit and t represents the time.

[0013] In an optional embodiment, the Hilbert spectrum is used to perform time-frequency spectrum visualization, amplitude analysis, oscillation pattern recognition and frequency transition detection.

[0014] The present invention also provides an electronic device, comprising: at least one processor; 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 any one of the interference source positioning methods based on VFTO analysis for a GIS system.

[0015] The present invention also provides a computer storage medium storing a computer program, wherein when the computer program is executed by a processor, the interference source positioning method based on VFTO analysis in a GIS system is implemented.

[0016] The beneficial effects of the present invention are: analyzing and processing the VFTO generated by the WAPI device to determine the interference source, which can cope with the complex industrial environment with strong electromagnetic interference and ensure the stability and reliability of the WAPI wireless environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flowchart of a method for locating interference sources based on VFTO analysis in a GIS system provided by an embodiment of the present invention;

[0018] Figure 2 A block diagram of an electronic device provided by an embodiment of the present invention.

[0019] Description of reference numerals:

[0020] 110. Processor; 120. Memory. DETAILED DESCRIPTION

[0021] The present invention is further described in detail below through the accompanying drawings and specific embodiments.

[0022] Transmission corridors cover an increasingly wide area, and transmission lines inevitably cross various ice-covered areas with complex terrain and cold climate. In recent years, with the increasing warming of the global climate, various extreme disasters have occurred frequently, and transmission tower collapse accidents have occurred from time to time in plateau areas. The main reason is that the transmission tower structure designed under the existing specifications can no longer effectively cope with the challenges of the new environment. It is urgent to propose a set of transmission tower standards that meet the strength requirements of the new environment, check the strength of the existing transmission tower structure, and provide guidance for subsequent upgrades and renovations.

[0023] like Figure 1As shown, according to an embodiment of the present invention, on the one hand, a method for locating interference sources based on VFTO analysis in a GIS system is provided, which is used for a WAPI device in a GIS system. The method for locating interference sources based on VFTO analysis in a GIS system comprises the following steps:

[0024] Step S101: extracting VFTO waveform data of access points of the wireless local area network security protocol of the GIS system.

[0025] Step S102: performing noise reduction processing on the VFTO waveform data;

[0026] Step S103: decomposing the denoised VFTO waveform data into several intrinsic mode functions of different frequency components.

[0027] Step S105: Perform Hilbert transform on each intrinsic mode function to construct a Hilbert spectrum.

[0028] Step S107: locate the interference source through the Hilbert spectrum based on the propagation characteristics of the interference signal and the physical layout of the system.

[0029] The interference source positioning method in this embodiment is particularly suitable for the wireless local area network security protocol (WLAN Authentication and Privacy Infrastructure, referred to as WAPI) equipment of the GIS system, and can effectively identify and locate the interference source appearing in the GIS system.

[0030] VFTO waveform data is extracted from the wireless LAN security protocol access point (WAPI-AP) of the GIS system. The VFTO waveform data contains the time domain characteristics of the interference signal and is the key information for analyzing the interference source.

[0031] Among them, the transient value of the voltage between WAPI-AP and ground, namely the VFTO waveform, can be measured by using a voltage probe and an oscilloscope when the circuit breaker or disconnector inside the GIS is opened or closed. The transient current of the POE network cable of WAPI-AP can also be measured by using a current probe and an oscilloscope. The transient current is presented as a voltage on the oscilloscope.

[0032] The extracted VFTO waveform data is subjected to noise reduction to improve the accuracy of subsequent analysis. The noise-reduced data will be decomposed into several intrinsic mode functions (IMFs) of different frequency components. This decomposition is based on the empirical mode decomposition (EMD) method, which can decompose complex signals into a series of simple basic modes.

[0033] A Hilbert Transform is then performed on each IMF to construct a Hilbert spectrum. The Hilbert Transform is a mathematical tool used to analyze the instantaneous frequency characteristics of a signal, while the Hilbert spectrum provides a detailed view of how the signal's frequency changes over time.

[0034] The constructed Hilbert spectrum can be used to accurately locate the interference source based on the propagation characteristics of the interference signal and the physical layout information of the GIS system. By analyzing the propagation path and attenuation characteristics of the signal, the possible location of the interference source can be inferred, thus providing an important reference for maintaining and optimizing the GIS system.

[0035] Among them, the propagation characteristics of the interference signal are as follows: when the isolation knife switch starts the opening operation at the voltage peak, since the voltage on the no-load bus is maintained at Em, and the voltage on the power supply side still changes in a sinusoidal manner, arc breakdown will occur when the rising speed of the transient overvoltage is greater than or equal to the electron avalanche critical value of SF6. At this time, the current will flow from the power supply side to the no-load bus side through the arc, causing the no-load side voltage to jump to synchronize with the power supply side voltage, accompanied by high-frequency oscillation, and generate VFTO. Since the isolation knife switch has no arc extinguishing ability, the arc will continue until the high-frequency current decays, and the arc will extinguish when it cannot maintain energy to continue burning. Since the voltage on the power supply side still changes in a sinusoidal manner and the voltage on the no-load side maintains the residual voltage at the moment of arc disconnection, when the recovery voltage between the contacts is greater than the breakdown voltage again, the contacts will be broken down again, and the cycle will repeat until the recovery voltage is no longer greater than the breakdown voltage between the contacts, the contacts are completely disconnected, and the opening ends.

[0036] The physical layout of the system refers to the physical layout of the GIS internal system, which directly affects the propagation path, peak value and waveform characteristics of VFTO by affecting the relative position of electrical equipment, grounding method, cable and conductor configuration, switch operation and other factors. When VFTO propagates in the GIS system, it may be reflected when encountering different electrical components, such as circuit breakers, busbars, wires, etc. The reflected wave interacts with the original wave, which may lead to an increase in the voltage waveform and produce a higher VFTO.

[0037] Furthermore, since the noise inside GIS is relatively strong, it will directly affect the key characteristics of the signal. In order to avoid the interference of noise on the IMF component, it is necessary to use the wavelet threshold denoising method for preprocessing before applying the EMD algorithm to decompose the signal, reduce noise interference, and avoid noise interference on the IMF component to ensure that the EMD decomposition result is more reliable.

[0038] The process of denoising VFTO waveform data is as follows:

[0039] Signal preprocessing: Check whether the signal contains obvious DC components or low-frequency interference. The low-frequency interference can be removed by a high-pass filter and the high-frequency components can be retained.

[0040] Wavelet decomposition: Select a wavelet basis suitable for VFTO signals, such as Daubechies db4 or Symlet sym6, to represent spike transient signals, and set the number of wavelet decomposition layers according to the signal length.

[0041] Noise threshold processing: The threshold is determined by the threshold formula:

[0042]

[0043] Among them, λ is the threshold, σ is the noise standard deviation, which can be estimated by the high-frequency wavelet coefficients, and N is the signal length.

[0044] Since the traditional threshold function is divided into soft threshold and hard threshold, the hard threshold is easy to cause the discontinuity of the function and the soft threshold is easy to cause the change of the value of the wavelet decomposition coefficient. In order to eliminate the discontinuity of the threshold function and make the function quickly approach the hard threshold function, the following threshold function can be used:

[0045]

[0046] Signal reconstruction: The denoised wavelet coefficients are used to reconstruct the signal using the inverse wavelet transform (IDWT) to ensure that the peak characteristics of VFTO are preserved and verified in the time and frequency domains.

[0047] Through the above processing, the noise reduction of VFTO waveform data is completed.

[0048] Based on step S105, each intrinsic mode function is subjected to Hilbert transform to construct a Hilbert spectrum, which specifically includes the following steps:

[0049] Step S1051: Perform Hilbert transform on each intrinsic mode function to extract time-frequency information, where the time-frequency information includes instantaneous frequency and instantaneous amplitude.

[0050] Step S1053: Accumulate the instantaneous frequencies and instantaneous amplitudes of all components of the intrinsic mode functions to construct a Hilbert spectrum:

[0051]

[0052] In the formula, δ(f-ω k (t)) is the unit impulse function, |IMF k (t)| is the instantaneous amplitude.

[0053] In this embodiment, each intrinsic mode function is subjected to Hilbert transform to extract the time-frequency information therein.

[0054] Time-frequency information refers to the frequency and amplitude at different time points, including instantaneous frequency and instantaneous amplitude.

[0055] Based on the extracted time-frequency information, the Hilbert spectrum is further constructed. The Hilbert spectrum is a tool that can describe the distribution of the signal in the time-frequency plane in detail. It combines the instantaneous frequency and instantaneous amplitude of the signal to form a three-dimensional representation, thus providing a powerful means for analyzing the local characteristics of the signal.

[0056] Step S107, locating the interference source through the Hilbert spectrum based on the propagation characteristics of the interference signal and the physical layout of the system, specifically includes the following steps:

[0057] Step S1071: extracting the temporal variation law of the instantaneous frequency from the intrinsic mode function to obtain the main characteristic frequency components of the VFTO waveform data after noise reduction;

[0058] Step S1073: According to the main characteristic frequency components, the characteristic frequencies and amplitudes of the test points are compared by Hilbert spectrum to determine the area with the strongest spectrum energy;

[0059] Step S1075: Based on the area with the strongest spectrum energy and the time starting point difference of the instantaneous frequency in the Hilbert spectrum, the propagation path of the VFTO waveform data at different test points is estimated to obtain the estimated distance. The calculation formula is as follows:

[0060] d=v×Δt.

[0061] Where d is the distance between the point to be measured and the interference source, positioning is the estimated distance, v is the signal propagation speed, and Δt is the arrival time difference of the instantaneous frequency.

[0062] Step S1077: Obtain the location of the interference source based on the estimated distance.

[0063] In this embodiment, the law of instantaneous frequency changing with time is extracted from the intrinsic mode function. This step can obtain the main characteristic frequency components in the VFTO waveform data after noise reduction. According to the main characteristic frequency components, the characteristic frequencies and amplitudes of different test points are compared by Hilbert transform technology to determine the area where the spectrum energy is most concentrated. Based on the area with the strongest spectrum energy, the time starting point difference of the instantaneous frequency in the Hilbert transform spectrum is further used to infer the propagation path of the VFTO waveform data at each test point, and finally calculate the specific distance between the interference source and the test point.

[0064] Based on the time-frequency information and Hilbert spectrum provided, an in-depth time-frequency characteristic analysis is performed. Through this analysis process, the precise distance between the interference source and the point to be measured can be calculated. Using the distance between the interference source and the point to be measured calculated in the previous step, a comparative analysis of the time-frequency energy is performed. By comparison, the specific location of the interference source can be further determined.

[0065] Step S107, locating the interference source through the Hilbert spectrum based on the propagation characteristics of the interference signal and the physical layout of the system, specifically includes the following steps:

[0066] Step S1072: Based on the Hilbert spectrum, compare the time-frequency energy distributions of different test points to obtain the frequency band with the maximum instantaneous energy.

[0067] Step S1074: obtaining a point to be tested according to the frequency band with the maximum instantaneous energy.

[0068] Step S1076: Analyze the attenuation law of the instantaneous energy of the characteristic frequency of the test point with the estimated distance, and establish an energy attenuation model, wherein the calculation formula of the instantaneous energy is as follows:

[0069]

[0070] Where, E(d) is the instantaneous energy at the distance from the measured point to the interference source, E 0 is the optimal initial energy, α m is the optimal attenuation coefficient, d is the estimated distance;

[0071] Step S1078: Based on the energy attenuation model, the location of the interference source is obtained by fitting the energy distribution.

[0072] Among them, by comparing the time-frequency energy distribution of different test points, the frequency band with the maximum instantaneous energy and the corresponding test point can be obtained, so as to locate the point with the maximum energy. The position with the maximum instantaneous energy is usually close to the interference source. After determining the frequency band with the maximum instantaneous energy, the specific test point can be located based on this frequency band. By analyzing the attenuation law of the instantaneous energy of the characteristic frequency of the test point with distance, an energy attenuation model can be established. Based on the established energy attenuation model, the specific location of the interference source can be reversely calculated by fitting the energy distribution.

[0073] Step S1078, based on the energy attenuation model, obtain the location of the interference source by fitting the energy distribution, specifically including the following steps:

[0074] Step S10781: Estimate the attenuation coefficient and initial energy.

[0075] Step S10783: According to the error function, the fitting attenuation coefficient and the initial energy are solved to obtain the optimal attenuation coefficient and the optimal initial energy, wherein the error function is as follows:

[0076]

[0077] Step S10785: Based on the optimal attenuation coefficient and the initial energy, the estimated distance is obtained, and the calculation formula is as follows:

[0078]

[0079] In the formula, E 0 is the optimal initial energy, E 1 is the energy of a certain point to be measured, E i is the instantaneous energy of the i-th measured point at the interference source, d i is the distance between the i-th test point and the interference source, α m is the optimal attenuation coefficient, and d is the estimated distance.

[0080] Step S10787: Obtain the location of the interference source based on the estimated distance.

[0081] In the process of applying the energy attenuation model to locate the interference source, the fitting process can be achieved through the least squares method.

[0082] Choose an initial guess: by estimating the attenuation coefficient and initial energy from some known propagation properties or measurements.

[0083] Minimum error: Use the least squares method to solve the fitting parameter α m and E 0 , so that the error between the predicted energy value and the actual measured energy value is minimized:

[0084]

[0085] By minimizing this error function, we can get the optimal α m and E 0 .

[0086] Among them, the least squares method is used to fit, and the α is determined m and E 0 .

[0087] Infer the location of the interference source: Infer the location of the interference source through the known measurement point energy data and the fitted energy attenuation model:

[0088]

[0089] The estimated distance calculated in this embodiment can be compared with the estimated distance calculated in the previous step. For the convenience of explanation, the estimated distance calculated in the previous step is named the first estimated distance, and the estimated distance calculated in the subsequent step is named the second estimated distance. The first estimated distance is compared with the second estimated distance. Only when the first estimated distance is close to the second estimated distance, the interference source is determined and the positioning will be more accurate. If the difference between the first estimated distance and the second estimated distance is large, it is necessary to continue to calculate the second estimated distance until the difference between the second estimated distance and the first estimated distance is within the preset range.

[0090] Based on step S103, the denoised VFTO waveform data is decomposed into several intrinsic mode functions of different frequency components, which specifically includes the following steps:

[0091] Step S1031: Decompose the VFTO waveform data into time series signals by using the EMD algorithm to obtain a series of intrinsic mode functions. The calculation formula is as follows:

[0092]

[0093] Where ξ(t) is the original signal, IMF i are K intrinsic mode functions, r K It is the remainder after subtracting the IMF from the original signal.

[0094] In this embodiment, the waveform signal is decomposed into IMFs by using the EMD algorithm.

[0095] Apply the EMD algorithm to the preprocessed VFTO waveform and obtain a series of intrinsic mode functions IMFs. The two conditions for judging the termination of the EMD algorithm program are: Condition 1: The average value of the mean line approaches 0, and the difference with 0 is generally <0.1. Condition 2: The difference between the number of extreme points of the original signal and the number of intersections of the original signal with y=0 cannot be greater than 1. When a certain IMF is found to be a monotonic function or lacks a maximum / minimum point, the program can be terminated.

[0096] In general, the Hilbert transform H[x(t)] of the original signal x(t) is usually written as:

[0097] z(t)=x(t)+jH[x(t)].

[0098] Among them, x(t) is called the real part of the complex signal z(t), H[x(t) is called the imaginary part of the complex signal z(t), and z(t) is called the analytic signal of x(t).

[0099] Through the above steps, the original signal x(t) is decomposed into several intrinsic mode functions IMFs. Each IMF can be regarded as a frequency component of the signal, and these frequency components vary locally.

[0100] Based on step S1051, Hilbert transform is performed on each intrinsic mode function to extract time-frequency information, where the time-frequency information includes instantaneous frequency and instantaneous amplitude, specifically including the following steps:

[0101] Step S10511: Assume that a component of an intrinsic mode function is IMF k (t), then the result of Hilbert transform is:

[0102]

[0103] Where H represents the Hilbert transform operation, IMF k (t) is the kth intrinsic mode function of the signal.

[0104] Step S10513: Obtain instantaneous frequency and instantaneous amplitude through Hilbert transform.

[0105] The calculation formula of instantaneous frequency is as follows:

[0106]

[0107] Wherein, arg() represents the phase operation.

[0108] The calculation formula of instantaneous amplitude is as follows:

[0109]

[0110] In the formula, j is an imaginary unit and t represents the time.

[0111] In this embodiment, a Hilbert transform is performed on each IMF to extract the instantaneous frequency distribution in the transient overvoltage waveform. The instantaneous frequency and instantaneous amplitude of each IMF can be obtained through the Hilbert transform, and the Hilbert spectrum can be constructed. The Hilbert transform can provide a complex analytical signal of the signal, thereby revealing the instantaneous characteristics of the signal such as the instantaneous frequency and instantaneous amplitude.

[0112] For each IMF component IMF k (t) First, we need to calculate the complex analytic signal of the signal. The complex analytic signal can be represented by the combination of the original signal and the Hilbert transform:

[0113]

[0114] Where j is an imaginary unit, IMF k (t) is the kth intrinsic mode function (IMF) of the signal, It is the IMF k Hilbert transform of (t).

[0115] In the process of calculating the instantaneous amplitude, the amplitude of the complex analytical signal is the instantaneous amplitude, which represents the instantaneous strength and amplitude of the signal at each moment t. It is the modulus of the complex signal, that is, the absolute value of the complex number. The calculation formula is as follows:

[0116]

[0117] Furthermore, time-frequency spectrum visualization, amplitude analysis, oscillation pattern recognition and frequency transition detection are performed through Hilbert spectrum.

[0118] The Hilbert spectrum is a time-frequency diagram. The following can be done by constructing the time-frequency diagram:

[0119] (1) Time-frequency spectrum visualization: The Hilbert spectrum of a signal is visualized into a two-dimensional image by drawing a time-frequency graph, where the X-axis represents time, the Y-axis represents frequency, and the color or brightness represents the amplitude or energy intensity. Therefore, the changes in the frequency components of the signal in different time periods can be intuitively observed, such as frequency transitions or frequency change trends, which helps to locate the time when abnormal events occur.

[0120] (2) Amplitude analysis: In the time-frequency spectrum, the amplitude is usually represented by color or brightness. Therefore, the transient amplitude changes corresponding to each IMF can be directly viewed on the time-frequency spectrum. The sudden increase in amplitude can be used to judge electrical disturbances or fault events in a short period of time; and the rapid decay of amplitude can be used for subsequent analysis of VFTO.

[0121] (3) Oscillation pattern recognition: When frequency components appear repeatedly in certain time periods in the time-frequency diagram, it may represent periodic oscillations; and when the oscillation frequency changes in different time periods, the intensity of the oscillation can be observed.

[0122] (4) Frequency transition detection: Observing the frequency transition points on the time-frequency spectrum can be used to determine drastic changes in the system state; the frequency transition increase or decrease and the amplitude of the jump frequency can provide clues for fault diagnosis.

[0123] On the other hand, Figure 2 As shown, the present invention also provides an electronic device, comprising: at least one processor; 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 any one of the interference source locating methods based on VFTO analysis in a GIS system.

[0124] On the other hand, the present invention also proposes a computer storage medium storing a computer program, which, when executed by a processor, implements any one of the interference source positioning methods based on VFTO analysis in a GIS system.

[0125] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM). The various embodiments in this specification are described in a progressive manner, and the same and similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0126] The above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the invention.

Claims

1. A method for locating interference sources based on VFTO analysis in a GIS system, used in a WAPI device of a GIS system, characterized in that: The method comprises: Extract VFTO waveform data from the wireless LAN security protocol AP of the GIS system; Performing noise reduction processing on the VFTO waveform data; Decomposing the VFTO waveform data after noise reduction into eigenmode functions of a plurality of different frequency components; Performing Hilbert transformation on each of the intrinsic mode functions to construct a Hilbert spectrum; The Hilbert spectrum is used to locate the interference source based on the propagation characteristics of the interference signal and the physical layout of the system.

2. The interference source positioning method based on VFTO analysis in a GIS system according to claim 1 is characterized in that: Performing a Hilbert transform on each of the intrinsic mode functions to construct a Hilbert spectrum includes: Performing Hilbert transform on each of the intrinsic mode functions to extract time-frequency information, wherein the time-frequency information includes instantaneous frequency and instantaneous amplitude; The instantaneous frequencies and instantaneous amplitudes of all the components of the intrinsic mode functions are accumulated to construct the Hilbert spectrum: In the formula, δ(f-ω k (t)) is the unit impulse function, |IMF k (t)| is the instantaneous amplitude.

3. The interference source positioning method based on VFTO analysis of the GIS system according to claim 2 is characterized in that: Through the Hilbert spectrum, based on the propagation characteristics of the interference signal and the physical layout of the system, the interference source is located, specifically including: Extracting the variation law of instantaneous frequency over time from the intrinsic mode function to obtain the main characteristic frequency components of the VFTO waveform data after noise reduction; According to the main characteristic frequency components, the characteristic frequencies and amplitudes of the test points are compared by the Hilbert spectrum to determine the area with the strongest spectrum energy; Based on the area with the strongest spectrum energy and the time starting point difference of the instantaneous frequency in the Hilbert spectrum, the propagation path of the VFTO waveform data at different test points is inferred to obtain the inferred distance. The calculation formula is as follows: d = v × Δt; In the formula, d is the distance between the point to be measured and the interference source, positioning is the estimated distance, v is the signal propagation speed, and Δt is the arrival time difference of the instantaneous frequency; The position of the interference source is obtained according to the estimated distance.

4. The interference source positioning method based on VFTO analysis in a GIS system according to claim 2 is characterized in that: Through the Hilbert spectrum, based on the propagation characteristics of the interference signal and the physical layout of the system, the interference source is located, specifically including: Based on the Hilbert spectrum, the time-frequency energy distribution of different test points is compared to obtain the frequency band with the maximum instantaneous energy; Obtaining a point to be tested according to the frequency band with the maximum instantaneous energy; Analyze the attenuation law of the instantaneous energy of the characteristic frequency of the test point with distance, and establish an energy attenuation model; Based on the energy attenuation model, the position of the interference source is obtained by fitting the energy distribution, wherein the calculation formula of the instantaneous energy is as follows: In the formula, E(d) is the instantaneous energy at the distance from the interference source to the measured point, E0 is the optimal initial energy, α m is the optimal attenuation coefficient, and d is the estimated distance.

5. The interference source location method based on VFTO analysis in a GIS system according to claim 4 is characterized in that: Based on the energy attenuation model, obtaining the position of the interference source by fitting the energy distribution specifically includes: Estimate attenuation coefficients and initial energies; According to the error function, the fitting attenuation coefficient and the initial energy are solved to obtain the optimal attenuation coefficient and the optimal initial energy, wherein the error function is as follows: Based on the optimal attenuation coefficient and the optimal initial energy, the estimated distance is obtained, and the calculation formula is as follows: In the formula, E0 is the optimal initial energy, E1 is the energy of a certain point to be measured, and E i is the instantaneous energy of the i-th measured point at the interference source, d i is the distance between the i-th test point and the interference source; α m is the optimal attenuation coefficient, d is the estimated distance; The position of the interference source is obtained based on the estimated distance.

6. The interference source location method based on VFTO analysis in a GIS system according to claim 2 is characterized in that: Performing Hilbert transform on each of the intrinsic mode functions to extract time-frequency information, where the time-frequency information includes instantaneous frequency and instantaneous amplitude, specifically including: Let the component of an intrinsic mode function be IMF k (t), then the result of Hilbert transform is: Where H represents the Hilbert transform operation, IMF k (t) is the kth intrinsic mode function of the signal; Obtaining instantaneous frequency and instantaneous amplitude through the Hilbert transform; The calculation formula of the instantaneous frequency is as follows: In the formula, arg() represents the phase operation; The calculation formula of the instantaneous amplitude is as follows: In the formula, j is an imaginary unit and t represents the time.

7. The interference source positioning method based on VFTO analysis of a GIS system according to any one of claims 1 to 6, characterized in that: The VFTO waveform data after noise reduction is decomposed into several intrinsic mode functions of different frequency components, specifically including: The VFTO waveform data after noise reduction is decomposed into a time series signal by the EMD algorithm to obtain a plurality of intrinsic mode functions, and the calculation formula is as follows: Where ξ(t) is the original signal, IMF i are K intrinsic mode functions, r K It is the remainder after subtracting the IMF from the original signal.

8. The interference source positioning method based on VFTO analysis of a GIS system according to any one of claims 1 to 6, characterized in that: The Hilbert spectrum is used to perform time-frequency spectrum visualization, amplitude analysis, oscillation pattern recognition and frequency transition detection.

9. An electronic device, characterized in that: include: at least one processor; a memory communicatively coupled 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 interference source positioning method based on VFTO analysis of the GIS system as described in any one of claims 1 to 8.

10. A computer storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a processor, an interference source positioning method based on VFTO analysis in a GIS system as described in any one of claims 1 to 8 is implemented.

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