A spectrum monitoring and interference analysis method for power grid wireless communications

Abstract

The present invention discloses a spectrum monitoring and interference analysis method for power grid wireless communications, specifically relating to the field of wireless spectrum monitoring technology. The method outputs an eddy current distribution parameter set based on the power frequency magnetic field intensity distribution data of a monitoring point; synchronously collects spectrum signals and power frequency magnetic flux density signals; calculates the high-frequency harmonic frequency characteristics of secondary radiation generated by spectrum monitoring equipment under the power frequency magnetic field, and generates an eddy current characteristic spectrum line diagram; extracts the frequency band energy value matching the eddy current characteristic spectrum line diagram from the spectrum signal, and calculates the contamination ratio of the secondary radiation to the spectrum signal in combination with the power frequency magnetic flux density signal; eliminates the contamination signal component according to the contamination ratio, and outputs a true spectrum; performs a joint scan on the true spectrum, extracts the modulation characteristics and spatial orientation of the residual interference signal, and generates an interference source location report. The method solves the problem of true spectrum signal distortion caused by eddy current secondary radiation under the power frequency magnetic field environment, and improves the accuracy and reliability of spectrum monitoring and interference analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless spectrum monitoring, and more particularly to a spectrum monitoring and interference analysis method for power grid wireless communications. Background Art

[0002] In current spectrum monitoring of power grid wireless communications, especially when monitoring equipment is deployed in power frequency magnetic field environments such as high-voltage substations, spectrum measurement results often have authenticity deviations.

[0003] Existing technologies mainly focus on the extraction of exogenous features of environmental electromagnetic interference, but ignore the inductive response problem generated by the spectrum monitoring equipment itself in the industrial frequency alternating magnetic field, especially the eddy current effect formed by the equipment structure under the action of the strong magnetic field, which seriously affects the accurate reconstruction of the actual electromagnetic environment and the identification of interference sources.

[0004] In order to solve the above problems, a technical solution is now provided. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a spectrum monitoring and interference analysis method for power grid wireless communication to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A spectrum monitoring and interference analysis method for power grid wireless communications includes the following steps:

[0008] S1: Based on the power frequency magnetic field intensity distribution data of the monitoring point, the eddy current distribution model of the spectrum monitoring equipment is established, and the eddy current distribution parameter set induced by the power frequency magnetic field is output;

[0009] S2: Collects the spectrum signal of the RF receiving channel of the spectrum monitoring device and the power frequency magnetic flux density signal of the magnetic field sensing channel, and aligns the sampling points using a phase synchronization algorithm;

[0010] S3: Calculate the high-frequency harmonic frequency characteristics of the secondary radiation generated by the spectrum monitoring equipment under the power frequency magnetic field based on the eddy current distribution parameter set, and generate an eddy current characteristic spectrum line diagram;

[0011] S4: Based on the spectrum signal, the frequency band energy value that matches the eddy current characteristic spectrum line diagram is extracted, and combined with the power frequency magnetic flux density signal, the pollution ratio of the secondary radiation generated by the spectrum monitoring equipment under the power frequency magnetic field to the spectrum signal is calculated;

[0012] S5: Based on the pollution ratio, the contamination signal components in the spectrum signal are eliminated and the purified real environment spectrum is output;

[0013] S6: Perform a time-frequency joint scan on the purified real environment spectrum to detect the modulation characteristics and spatial orientation of the residual interference signal, and generate a power grid wireless communication interference source location report.

[0014] In a preferred embodiment, S1 is specifically:

[0015] Collect power frequency magnetic field intensity distribution data at the monitoring point where spectrum monitoring equipment is installed in high-voltage substations;

[0016] Based on the structural parameter information of the spectrum monitoring equipment in the high-voltage substation and the power frequency magnetic field intensity distribution data, an eddy current distribution model of the spectrum monitoring equipment under the action of the power frequency magnetic field is established;

[0017] By analytically solving the electromagnetic induction equation, the eddy current distribution parameter set of the spectrum monitoring equipment in the power frequency magnetic field environment is obtained.

[0018] In a preferred embodiment, S2 is specifically:

[0019] Collect spectrum signals in the RF receiving channel of spectrum monitoring equipment in high-voltage substations;

[0020] Collect the power frequency magnetic flux density signal in the magnetic field sensing channel of the spectrum monitoring equipment in the high-voltage substation;

[0021] A phase synchronization algorithm based on a time synchronization reference signal is used to synchronously process the spectrum signal collected by the RF receiving channel of the spectrum monitoring equipment and the power frequency magnetic flux density signal collected by the magnetic field sensing channel, and align the sampling points of the spectrum signal and the power frequency magnetic flux density signal.

[0022] In a preferred embodiment, S3 is specifically:

[0023] Based on the eddy current distribution parameter set and the structural parameters of the spectrum monitoring equipment in the high-voltage substation, the electromagnetic secondary radiation calculation model is used to calculate the high-frequency harmonic frequency characteristics generated by the spectrum monitoring equipment under the action of the power frequency magnetic field. The high-frequency harmonic frequency characteristics include the high-frequency harmonic frequency value and the corresponding radiation amplitude value.

[0024] Based on Fourier transform and spectrum analysis methods, an eddy current characteristic spectrum line diagram reflecting the characteristics of high-frequency harmonic frequency points is generated; the horizontal axis of the eddy current characteristic spectrum line diagram represents the harmonic frequency, and the vertical axis represents the electromagnetic radiation amplitude value corresponding to the harmonic frequency.

[0025] In a preferred embodiment, S4 is specifically:

[0026] Perform frequency domain processing on the spectrum signal, and identify the frequency band energy value corresponding to the eddy current characteristic spectrum line diagram in the spectrum signal according to the high-frequency harmonic frequency point characteristics of the eddy current characteristic spectrum line diagram;

[0027] Calculate the power frequency magnetic flux density change rate of the power frequency magnetic flux density signal of the magnetic field sensing channel;

[0028] Based on the frequency band energy value and the rate of change of the power frequency magnetic flux density, the pollution ratio of the spectrum signal caused by the secondary radiation of eddy current generated by the spectrum monitoring equipment under the action of the power frequency magnetic field is calculated.

[0029] In a preferred embodiment, S5 is specifically:

[0030] According to the pollution ratio of the eddy current secondary radiation generated by the spectrum monitoring equipment under the action of the power frequency magnetic field to the spectrum signal, the signal component contaminated by the eddy current secondary radiation corresponding to the eddy current characteristic spectrum line diagram in the spectrum signal is identified;

[0031] Based on the spectrum filtering method, the signal components contaminated by the secondary radiation of eddy current are removed from the spectrum signal;

[0032] The spectrum signal after removing the signal components contaminated by the secondary radiation of the eddy current is used as the purified real environment spectrum.

[0033] In a preferred embodiment, S6 is specifically:

[0034] Perform joint scanning processing in the time domain and frequency domain on the purified real environment spectrum to obtain the residual interference signal in the real environment spectrum;

[0035] Modulation recognition is used to extract characteristic parameters of residual interference signals in the real environment spectrum;

[0036] The spatial orientation of the residual interference signal is determined by using the spatial spectrum estimation method combined with the spatial coordinates of the spectrum monitoring equipment in the high-voltage substation;

[0037] The characteristic parameters and spatial azimuth of the residual interference signal are integrated to form a positioning report of the power grid wireless communication interference source.

[0038] The technical effects and advantages of the spectrum monitoring and interference analysis method for power grid wireless communication of the present invention are as follows:

[0039] An eddy current distribution model is established based on power-frequency magnetic field intensity distribution data, enabling quantitative modeling of the eddy current behavior induced by spectrum monitoring equipment in high-intensity magnetic field environments and improving the controllability of interference sources within the spectrum monitoring equipment itself. By collecting spectrum signals and power-frequency magnetic flux density signals and performing phase synchronization processing, the temporal consistency of multi-source data is ensured, providing a time reference for interference tracing. High-frequency harmonic frequency characteristics are inferred based on the eddy current distribution parameter set and an eddy current characteristic spectrum is generated, helping to accurately characterize the secondary radiated interference characteristics of the spectrum monitoring equipment. The spectrum signals are matched with the eddy current characteristic spectrum and combined with the power-frequency magnetic flux density signal to quantify the contamination ratio and effectively isolate the nonlinear distortion introduced by the spectrum monitoring equipment itself. The contamination ratio is used to remove contaminated signal components, improving the authenticity and usability of the spectrum data. Residual interference is identified and spatially located in the cleaned real-world spectrum, enhancing the ability to track interference sources in power grid environments. This effectively addresses the issue of equipment-induced interference caused by power-frequency magnetic fields in high-voltage substations, improving the accuracy of reconstructing the real electromagnetic environment and locating interference sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a schematic diagram of a spectrum monitoring and interference analysis method for power grid wireless communications according to the present invention. DETAILED DESCRIPTION

[0041] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0042] Example

[0043] Figure 1 The present invention provides a spectrum monitoring and interference analysis method for power grid wireless communication, which includes the following steps:

[0044] S1: Based on the power frequency magnetic field intensity distribution data of the monitoring point, the eddy current distribution model of the spectrum monitoring equipment is established, and the eddy current distribution parameter set induced by the power frequency magnetic field is output;

[0045] S2: Collects the spectrum signal of the RF receiving channel of the spectrum monitoring device and the power frequency magnetic flux density signal of the magnetic field sensing channel, and aligns the sampling points using a phase synchronization algorithm;

[0046] S3: Calculate the high-frequency harmonic frequency characteristics of the secondary radiation generated by the spectrum monitoring equipment under the power frequency magnetic field based on the eddy current distribution parameter set, and generate an eddy current characteristic spectrum line diagram;

[0047] S4: Based on the spectrum signal, the frequency band energy value that matches the eddy current characteristic spectrum line diagram is extracted, and combined with the power frequency magnetic flux density signal, the pollution ratio of the secondary radiation generated by the spectrum monitoring equipment under the power frequency magnetic field to the spectrum signal is calculated;

[0048] S5: Based on the pollution ratio, the contamination signal components in the spectrum signal are eliminated and the purified real environment spectrum is output;

[0049] S6: Perform a time-frequency joint scan on the purified real environment spectrum to detect the modulation characteristics and spatial orientation of the residual interference signal, and generate a power grid wireless communication interference source location report.

[0050] S1: Based on the power frequency magnetic field intensity distribution data of the monitoring point, the eddy current distribution model of the spectrum monitoring equipment is established, and the eddy current distribution parameter set induced by the power frequency magnetic field is output, including:

[0051] Collect power frequency magnetic field intensity distribution data at the monitoring point where spectrum monitoring equipment is installed in high-voltage substations;

[0052] Spectrum monitoring equipment is deployed in high-voltage substations, which include transformers, high-voltage switches, busbars, supporting structural supports, and metal grounding devices. The presence of power-frequency currents in high-voltage substations, as they flow through the busbars, conductors, and equipment, generates a distinct power-frequency magnetic field intensity distribution within the substation. This power-frequency magnetic field intensity distribution data describes the strength characteristics of the magnetic field at various points within the substation's three-dimensional space.

[0053] A magnetic field measuring instrument is used for spatial dot matrix measurement. Specifically, an industrial frequency magnetic field measuring instrument is selected. The measurement principle is to use the magnitude of the induced electromotive force in the coil of the magnetic field sensor device to determine the industrial frequency magnetic field strength. During the measurement process, the magnetic field measuring instrument is placed in the spatial area surrounding the deployment location of the spectrum monitoring equipment. A spatial measurement grid is constructed with the location of the spectrum monitoring equipment as the center. The spatial measurement grid is in the shape of a regular cube, and the measurement positions are arranged using a uniformly spaced measurement dot matrix. The spatial coordinates of each measurement position are determined by measurement with a laser rangefinder, and the spatial coordinate information of each measurement position is recorded. The spatial coordinate information includes the values in the vertical direction, height direction, and depth direction.

[0054] After determining the measurement locations, the power-frequency magnetic field strength is measured at each measurement location within the spatial measurement grid. At each measurement location, the magnetic field measuring instrument uses its built-in electromagnetic induction coil to measure the induced electromotive force (EMF) generated by the power-frequency magnetic field. Based on this induced EMF, the magnetic field strength at that measurement location is calculated. The formula for calculating magnetic field strength is: Magnetic field strength equals the induced EMF divided by the product of the coil area of the magnetic field measuring instrument and the power-frequency frequency. This measurement process is repeated for all measurement locations within the spatial measurement grid, and the magnetic field strength value at each measurement location is recorded one by one, forming a three-dimensional data set of the power-frequency magnetic field strength distribution.

[0055] The measured power-frequency magnetic field intensity distribution data set undergoes preprocessing, including denoising and smoothing, to eliminate abnormal values caused by external interference or instrument accuracy errors during the measurement process. Smoothing utilizes a spatial data interpolation method, using the Kriging interpolation algorithm. By considering the spatial correlation of magnetic field intensity between measurement points and the continuity of the numerical distribution, the smoothness of the power-frequency magnetic field intensity data is optimized to generate a continuous and smooth power-frequency magnetic field intensity distribution data field.

[0056] Based on the structural parameter information of the spectrum monitoring equipment in the high-voltage substation and the power frequency magnetic field intensity distribution data, an eddy current distribution model of the spectrum monitoring equipment under the action of the power frequency magnetic field is established;

[0057] Construct an eddy current distribution model for spectrum monitoring equipment in the power frequency magnetic field environment of a high-voltage substation. To develop this specific eddy current distribution model, first obtain the structural parameters of the spectrum monitoring equipment, including the dimensions of its metal casing, material conductivity, spatial installation location, and structural geometry. This structural parameter information is obtained from the equipment's structural design drawings and technical manuals for its materials. Using electromagnetic simulation software, an electromagnetic finite element simulation model of the spectrum monitoring equipment structure is constructed based on this structural parameter information.

[0058] In the electromagnetic finite element simulation model, the power frequency magnetic field intensity distribution data field is imported and applied as an input boundary condition to the electromagnetic finite element simulation model of the spectrum monitoring equipment. The electromagnetic simulation software uses a finite element algorithm to discretize the spectrum monitoring equipment structure into multiple units and solves Maxwell's equations for the electromagnetic field equations within each unit, including the relationship between electric field intensity and magnetic field intensity, eddy current density and conductivity, and frequency. Finite element iteration is used to solve the eddy current density distribution values for all units. By integrating the eddy current density distribution values within all units, the eddy current distribution characteristics of the entire spectrum monitoring equipment surface are obtained.

[0059] By analytically solving the electromagnetic induction equation, the eddy current distribution parameter set of the spectrum monitoring equipment in the power frequency magnetic field environment is obtained;

[0060] Based on the eddy current distribution characteristics on the surface of the spectrum monitoring equipment, the electromagnetic induction equation is analytically solved to refine the eddy current distribution parameters. The analytical solution steps of the electromagnetic induction equation are as follows: based on the characteristic distribution of eddy current density on the surface of the spectrum monitoring equipment, the electromagnetic induction law is applied to calculate the induced electromotive force and eddy current distribution generated by each unit eddy current, and the eddy current path and current density amplitude and phase distribution characteristics are determined. The analytical solution method of the electromagnetic induction equation is to expand the integral term in the electromagnetic induction equation and solve the eddy current distribution of each unit based on the conductivity, magnetic permeability and magnetic field frequency of the metal structure of the spectrum monitoring equipment.

[0061] The eddy current density, amplitude, phase, and spatial position data analytically calculated by all units are integrated to form a complete eddy current distribution parameter set for spectrum monitoring equipment in a power-frequency magnetic field environment. This eddy current distribution parameter set includes the intensity, direction, and phase distribution characteristics of eddy currents at every location on the spectrum monitoring equipment's surface, providing data support for analyzing the secondary radiated interference spectrum caused by eddy currents in spectrum monitoring equipment.

[0062] S2: Collects the spectrum signal of the RF receiving channel of the spectrum monitoring device and the power frequency magnetic flux density signal of the magnetic field sensing channel, and aligns the sampling points using a phase synchronization algorithm, including:

[0063] Collect spectrum signals in the RF receiving channel of spectrum monitoring equipment in high-voltage substations;

[0064] The spectrum monitoring equipment includes two independent data acquisition channels: an RF receiving channel and a magnetic field sensing channel. The RF receiving channel is used to receive wireless spectrum signals generated by secondary radiation of the power frequency magnetic field and environmental signals within the high-voltage substation space. The magnetic field sensing channel is used to collect real-time power frequency magnetic flux density signals at specific monitoring locations within the high-voltage substation.

[0065] In the spectrum monitoring equipment's RF receiving channel, a broadband RF receiver is used to continuously and in real time collect wireless electromagnetic signals from the substation environment. This broadband RF receiver consists of a high-frequency receiving antenna, a low-noise amplifier (LNA), an intermediate-frequency (IF) filter, and a high-precision analog-to-digital converter (ADC). The HF antenna is a wideband omnidirectional antenna designed to capture omnidirectional RF signals. The LNA's gain is optimized to ensure stable signal amplification and a signal-to-noise ratio within a reasonable range. The IF filter uses a bandpass structure to limit the frequency range of the received signal and filter out spurious signals outside this range. The high-precision ADC provides high-resolution digital signal output.

[0066] The RF receiving channel feeds the received analog RF signal via the antenna to a low-noise amplifier for initial amplification. The signal then passes through a bandpass IF filter and is then transmitted to a high-precision analog-to-digital converter for conversion, generating a spectrum signal data stream. This entire acquisition process is continuous and uninterrupted, ensuring that the spectrum data accurately reflects the actual electromagnetic conditions within the substation environment in real time.

[0067] Collect the power frequency magnetic flux density signal in the magnetic field sensing channel of the spectrum monitoring equipment in the high-voltage substation;

[0068] In the magnetic field sensing channel, the magnetic field sensor uses a high-precision Hall-effect magnetic flux density sensor, capable of accurately capturing the magnetic flux density signal generated by changes in the power frequency magnetic field at the monitoring location within the substation in real time. The magnetic field sensor is fixedly installed at a designated location near the spectrum monitoring equipment to accurately monitor the real-time changes in magnetic flux density at the designated location.

[0069] The power-frequency magnetic flux density signal collected by the magnetic field sensing channel is converted into a digital data stream in real time using a high-precision analog-to-digital converter. This conversion utilizes the same high sampling accuracy and frequency as the RF receiving channel, ensuring the same precision during synchronization between the two data streams. The collected magnetic flux density data is a continuous, high-resolution time series, fully documenting the detailed changes in magnetic field intensity over time.

[0070] A phase synchronization algorithm based on a time synchronization reference signal is used to synchronize the spectrum signal collected by the spectrum monitoring equipment's RF receiving channel with the power frequency magnetic flux density signal collected by the magnetic field sensing channel, aligning the sampling points of the spectrum signal and the power frequency magnetic flux density signal.

[0071] To effectively synchronize the signals collected by these two channels, a phase synchronization algorithm based on a time synchronization reference signal is used. This time synchronization reference signal is fed simultaneously into the RF receiving channel and the magnetic field sensing channel, serving as a common clock reference for both channels, ensuring that the clock references for the collected data are completely consistent.

[0072] When implementing the phase synchronization algorithm, a standard synchronous clock pulse signal is first selected as the synchronization reference. Based on this synchronous clock pulse signal, a digital phase-locked loop method is used to synchronize the sampling times of the spectrum signal and the power-frequency magnetic flux density signal. The sampling points of the spectrum signal data stream and the magnetic flux density signal data stream are initially collected. Then, the digital phase-locked loop algorithm is used to calculate the phase difference between the two channel sampling signals relative to the synchronization reference. This phase difference is compensated and adjusted in real time to achieve precise phase alignment between the two signal sampling points.

[0073] S3: Based on the eddy current distribution parameter set, calculate the high-frequency harmonic frequency characteristics of the secondary radiation generated by the spectrum monitoring equipment in the power frequency magnetic field, and generate an eddy current characteristic spectrum line diagram, including:

[0074] Based on the eddy current distribution parameter set and the structural parameters of the spectrum monitoring equipment in the high-voltage substation, the electromagnetic secondary radiation calculation model is used to calculate the high-frequency harmonic frequency characteristics generated by the spectrum monitoring equipment under the action of the power frequency magnetic field;

[0075] The electromagnetic secondary radiation calculation model is a frequency domain finite element analysis model. The frequency domain finite element analysis model is suitable for calculating the electromagnetic secondary radiation characteristics of complex structures.

[0076] The electromagnetic field radiation characteristics are solved in the frequency domain using the eddy current distribution parameter set on the surface of the spectrum monitoring equipment as the radiation source input via Maxwell's equations. The frequency domain expression of Maxwell's equations includes the Helmholtz equation for the spatial distribution relationship between electric and magnetic field intensities. The structural parameter information and spatial boundary conditions of the spectrum monitoring equipment are used to calculate the domain and electromagnetic field constraints. Spatial boundary conditions refer to the spatial calculation boundary conditions of the model's environment that need to be set when establishing the electromagnetic finite element simulation model and electromagnetic secondary radiation calculation model of the spectrum monitoring equipment. These include: the scope of the simulation calculation area, i.e., the size and boundary position of the space surrounding the spectrum monitoring equipment in the high-voltage substation; the propagation and reflection conditions of electromagnetic waves at the boundaries of the simulation area; and other existing high-voltage substation structures.

[0077] During calculations, the electromagnetic secondary radiation calculation model discretizes the spectrum monitoring equipment into a large number of tiny cells, applies eddy current parameters to each cell, and connects the cells through continuity boundary conditions to ensure continuous and stable calculations. The discretization process uses a meshing method, where the mesh cell size is selected based on the frequency range of the spectrum monitoring equipment's radiation to ensure that the mesh cell size is smaller than the wavelength of the electromagnetic wave in the material, thereby improving the accuracy of the calculation results.

[0078] After solving the eddy current distribution parameter set, the electromagnetic secondary radiation calculation model obtains the high-frequency harmonic frequency characteristics radiated by the surface of the spectrum monitoring equipment structure under the action of the power frequency magnetic field. The high-frequency harmonic frequency characteristics include high-frequency harmonic frequency values and corresponding radiation amplitude values. High-frequency harmonic frequency values are high-frequency harmonic frequencies that are integer multiples of the power frequency, excited by the nonlinear effects of eddy currents induced by the power frequency magnetic field. The radiation amplitude values of each harmonic frequency are determined by the electromagnetic field calculation results of the corresponding frequency. The amplitude value is calculated by integrating the amplitude of the spatial electromagnetic field vector field distribution at the specified radiation field point in the model.

[0079] Based on Fourier transform and spectrum analysis methods, an eddy current characteristic spectrum line diagram reflecting the high-frequency harmonic frequency characteristics is generated;

[0080] Before Fourier transform, the high-frequency harmonic frequency features are preprocessed, including data interpolation and smoothing. Data interpolation uses linear interpolation to compensate for missing values between discrete frequency points that may occur during calculation. Smoothing uses a moving average filter to reduce amplitude anomalous points caused by calculation or measurement errors, ensuring the generated eddy current characteristic spectrum curve is continuous and stable.

[0081] The Fourier transform process involves performing a frequency-domain transformation on the radiation amplitude corresponding to the processed high-frequency harmonic frequency values. This transformation process includes the following steps: first, determining the relationship between the electromagnetic field intensity and frequency at a specific spatial location of the spectrum monitoring device; then, inputting the processed high-frequency harmonic frequency characteristics into the Fourier transform formula; the Fourier transform formula is: the spectrum amplitude value is equal to the frequency distribution relationship of the amplitude obtained by integrating the processed high-frequency harmonic frequency characteristics over the entire frequency range. The transformation result is presented as a spectrum graph, namely the eddy current characteristic spectrum line graph. The horizontal axis of the eddy current characteristic spectrum line graph represents the harmonic frequency, and the vertical axis represents the electromagnetic radiation amplitude value corresponding to the harmonic frequency.

[0082] S4: Based on the spectrum signal extraction and the frequency band energy value that matches the eddy current characteristic spectrum line diagram, combined with the power frequency magnetic flux density signal, calculate the pollution ratio of the secondary radiation generated by the spectrum monitoring equipment in the power frequency magnetic field to the spectrum signal, including:

[0083] Perform frequency domain processing on the spectrum signal, and identify the frequency band energy value corresponding to the eddy current characteristic spectrum line diagram in the spectrum signal according to the high-frequency harmonic frequency point characteristics of the eddy current characteristic spectrum line diagram;

[0084] Frequency domain processing is implemented using the Fast Fourier Transform (FFT) algorithm. This involves sampling the spectrum signal data stream in segments. The sampling length is determined in conjunction with the sampling rate of the spectrum monitoring equipment to ensure that the resolution of the frequency domain analysis is sufficient to distinguish the frequency components of the spectrum signal.

[0085] The spectrum signal collected by the RF receiving channel is divided into several segments of fixed duration. A fast Fourier transform is performed within each segment. Specifically, the amplitude of the spectrum signal at each frequency point is calculated by multiplying the spectrum signal by the Fourier transform basis function within the corresponding time period. The result of this calculation forms a spectrum signal amplitude distribution curve, which represents the specific energy level at each frequency point in the spectrum signal.

[0086] Based on the high-frequency harmonic frequency features in the eddy current characteristic spectrum, the energy values of the frequency bands corresponding to the high-frequency harmonic frequency features in the eddy current characteristic spectrum are identified. Specifically, a spectrum matching algorithm is used. The spectrum matching algorithm multiplies the amplitude distribution curve of the spectrum signal with the eddy current characteristic spectrum point by point and then sums them to determine the correlation between the two. This allows the energy values of the spectrum signal corresponding to each high-frequency harmonic frequency point in the eddy current characteristic spectrum to be identified.

[0087] For each harmonic frequency point in the eddy current signature spectrum, the spectrum matching algorithm calculates the energy integral of the spectral signal within the corresponding frequency range. The formula for calculating the band energy value is: the squared amplitude of the spectral signal near a specific frequency point is integrated over a range around that specific frequency point. The integration frequency range extends over a certain frequency interval, centered at the frequency point of the eddy current signature spectrum. All band energy values constitute the set of band energy values in the spectral signal corresponding to the eddy current signature spectrum.

[0088] Calculate the power frequency magnetic flux density change rate of the power frequency magnetic flux density signal of the magnetic field sensing channel;

[0089] The power frequency magnetic flux density rate of change is calculated for the power frequency magnetic flux density signal collected by the magnetic field sensing channel. This is calculated using the time domain difference method, which calculates the ratio of the difference between the power frequency magnetic flux density signal at consecutive time points to the corresponding sampling time interval. The calculation formula is: the power frequency magnetic flux density rate of change is equal to the difference between the power frequency magnetic flux density signal values at adjacent sampling time points divided by the sampling time interval between adjacent sampling time points.

[0090] Based on the frequency band energy value and the rate of change of the power frequency magnetic flux density, calculate the pollution ratio of the spectrum signal caused by the secondary radiation of eddy current generated by the spectrum monitoring equipment under the action of the power frequency magnetic field;

[0091] The pollution ratio is calculated by regression analysis, using a multiple linear regression algorithm. The multiple linear regression algorithm can identify the linear dependence between the energy value of the spectrum signal frequency band and the rate of change of the power frequency magnetic flux density, thereby calculating the pollution ratio, specifically:

[0092] First, a multivariate linear regression model was established with the frequency band energy value as the dependent variable and the power frequency magnetic flux density change rate as the independent variable. The model parameters include the regression coefficient and the intercept. The model calculation formula is: the frequency band energy value is equal to the regression coefficient multiplied by the power frequency magnetic flux density change rate plus the intercept. The regression coefficient and intercept are obtained using the least squares method. The solution process is to minimize the sum of squared errors between the model-predicted frequency band energy value and the actual frequency band energy value.

[0093] After obtaining the regression coefficients corresponding to each frequency band through model calculation, the pollution ratio is calculated based on the regression coefficients. The pollution ratio is calculated as follows: the pollution ratio is equal to the regression coefficient multiplied by the rate of change of the power frequency magnetic flux density at the corresponding sampling time point, divided by the actual frequency band energy value.

[0094] S5: Based on the pollution ratio, the polluted signal components in the spectrum signal are eliminated and the purified real environment spectrum is output, including:

[0095] According to the pollution ratio of the eddy current secondary radiation generated by the spectrum monitoring equipment under the action of the power frequency magnetic field to the spectrum signal, the signal component contaminated by the eddy current secondary radiation corresponding to the eddy current characteristic spectrum line diagram in the spectrum signal is identified;

[0096] Based on the contamination ratio, a spectrum energy separation algorithm is used to identify the contaminated signal components in the spectrum signal. This algorithm multiplies the amplitude value corresponding to each frequency band in the spectrum signal amplitude distribution curve by the contamination ratio of that frequency band to obtain the amplitude value of the contaminated signal component caused by eddy current secondary radiation in each frequency band.

[0097] Based on the spectrum filtering method, the signal components contaminated by the secondary radiation of eddy current are removed from the spectrum signal;

[0098] The spectrum filtering method uses a notch filter algorithm. The working principle of the notch filter algorithm is to filter a specific contaminated frequency band in the spectrum domain to remove the contaminated signal component caused by the secondary radiation of the eddy current in the spectrum signal:

[0099] First, a filter is constructed based on a notch filtering algorithm. The filter's design parameters include the center frequency and bandwidth. The center frequency is chosen to correspond to the high-frequency harmonics in the eddy current characteristic spectrum, and the bandwidth is chosen to fully cover the pollution energy distribution range corresponding to the high-frequency harmonics.

[0100] The spectrum signal data stream is passed through a notch filter to perform filtering. The filtering process includes:

[0101] When the spectrum signal data stream passes through the notch filter, the amplitude value within the filter frequency range is attenuated to zero or close to zero, while the signal amplitude value within the frequency range outside the filter is retained without attenuation, so as to retain the energy information of the spectrum signal to the greatest extent.

[0102] The spectrum signal after removing the signal components contaminated by the secondary radiation of the eddy current is used as the purified real environment spectrum;

[0103] The spectrum signal data stream obtained after filtering is the spectrum signal after removing the signal component contaminated by the secondary radiation of the eddy current.

[0104] S6: Perform a time-frequency joint scan of the purified real-world spectrum to detect the modulation characteristics and spatial orientation of the residual interference signal, and generate a grid wireless communication interference source location report, including:

[0105] Perform joint scanning processing in the time domain and frequency domain on the purified real environment spectrum to obtain the residual interference signal in the real environment spectrum;

[0106] The purified real environment spectrum is scanned jointly in the time domain and frequency domain. The joint scan uses short-time Fourier transform analysis technology, specifically:

[0107] The purified real environment spectrum is divided into several continuous short-term windows, and the duration of each short-term window is set to a short time length that can reflect the transient characteristics of the residual interference signal, specifically an integer multiple of the power frequency period.

[0108] A Fourier transform operation is performed on the spectrum signal in each short time window to obtain a frequency-amplitude distribution diagram of each short time window.

[0109] Analyze the amplitude characteristics of specific sudden peak signals in the frequency-amplitude distribution graph. Define signals whose amplitude exceeds the threshold for the normal background signal amplitude as residual interference signals. The average amplitude value is calculated by summing the amplitude values of the normal background signal at each sampling point over a period of time and dividing it by the number of sampling points. The variance is the sum of the squares of the difference between the amplitude value at each sampling point and the average amplitude, divided by the number of sampling points. The normal background signal amplitude threshold is set to three times the average amplitude value plus the variance.

[0110] Modulation recognition is used to extract characteristic parameters of residual interference signals in the real environment spectrum;

[0111] A high-order cumulant modulation recognition algorithm is used to identify the modulation type and extract characteristic parameters of the identified residual interference signal. This algorithm is not susceptible to Gaussian white noise interference and is suitable for interference signal analysis in complex high-voltage substation environments.

[0112] Specifically, the data sequence of the identified residual interference signal is processed through fourth-order cumulants. The fourth-order cumulants are calculated by calculating the fourth-order moment of the residual interference signal data sequence. This is done by sequentially combining the time-domain values of the residual interference signal sampling points into the mean of the fourth-order product. This is then subtracted from the product of three second-order moments (e.g., three times the square of the second-order moment) to eliminate interference from lower-order statistical features on higher-order feature analysis, resulting in the fourth-order cumulant.

[0113] Perform characteristic statistical analysis on the calculated fourth-order cumulants and extract the amplitude and phase statistical characteristics of the cumulants to determine the modulation type of the residual interference signal (amplitude modulation, frequency modulation or phase modulation type).

[0114] Perform Fourier transform on the fourth-order cumulants and calculate the transformation result in the complex domain. Then, extract the amplitude and phase features from the transformation result in the complex domain. The amplitude feature is the modulus of the complex value, that is, the square root of the sum of the square of the real part and the square of the imaginary part; the phase feature is the argument of the complex value, that is, the inverse tangent of the ratio of the imaginary part to the real part.

[0115] Statistical features, including mean, standard deviation, and kurtosis, are calculated for both amplitude and phase features. A type match is performed based on a pre-established modulation feature database to determine whether the residual interference signal belongs to amplitude modulation, frequency modulation, or phase modulation.

[0116] For amplitude modulation, the envelope signal of the residual interference signal is analyzed and fast Fourier transform is performed to calculate the maximum peak frequency, which is the modulation frequency.

[0117] The carrier frequency is the center frequency of the main peak in the spectrum of the residual interference signal, which is determined by the peak position of the spectrum energy;

[0118] Bandwidth is defined as the width of the frequency interval corresponding to the time when the energy on both sides of the main peak of the residual interference signal spectrum drops to half of the maximum value;

[0119] The modulation index is determined by dividing the difference between the maximum and minimum amplitudes of the amplitude envelope signal by the sum of the maximum and minimum amplitudes.

[0120] For the frequency modulation type, the instantaneous frequency of the residual interference signal is Hilbert transformed to calculate the difference between the maximum and minimum values of the instantaneous frequency change, and then divided by the modulation frequency to determine the modulation index. The carrier frequency, modulation frequency, and bandwidth are determined in the same way as the amplitude modulation type.

[0121] For phase modulation, the maximum instantaneous phase change is calculated, which is the modulation index. The carrier frequency, modulation frequency, and bandwidth are determined in the same way as for amplitude modulation.

[0122] Key characteristic parameters include but are not limited to carrier frequency, modulation frequency, bandwidth and modulation index.

[0123] The spatial orientation of the residual interference signal is determined by using the spatial spectrum estimation method combined with the spatial coordinates of the spectrum monitoring equipment in the high-voltage substation;

[0124] The spatial spectrum estimation method selects a multiple signal classification algorithm, which is suitable for the precise spatial positioning of interference sources in complex electromagnetic environments.

[0125] The spatial array signals of the residual interference signal collected by the array antenna used in the spectrum monitoring equipment are input into the multiple signal classification algorithm. The array antenna is deployed on the spectrum monitoring equipment. The spatial coordinate information is measured using a laser rangefinder and an electronic compass and recorded as the three-dimensional spatial coordinate data of the high-voltage substation.

[0126] The covariance matrix of the spatial array signal is calculated using the spatial array signal, and then the eigenvalue decomposition is performed to divide the covariance matrix after the eigenvalue decomposition into a signal subspace and a noise subspace.

[0127] The spatial spectrum function is calculated using the noise subspace and array flow pattern vector. The spatial spectrum estimation function is used in spatial spectrum estimation algorithms (such as multiple signal classification algorithms) to analyze the spatial signal orientation. After obtaining the noise subspace from the signal received by the array antenna through eigenvalue decomposition, different spatial orientation angles are substituted into the array flow pattern vector and matrix-multiplied with the noise subspace. The inverse norm of the matrix product is then calculated to obtain the spatial spectrum estimate for each spatial orientation angle. The array flow pattern vector refers to the spatial phase characteristic vector of the array antenna element response when the array antenna receives an incident electromagnetic wave signal at a specific spatial orientation. This is obtained using the known array antenna structural parameters (element layout geometry, spacing between elements, number of elements) and wavelength in the spectrum monitoring equipment.

[0128] The spectral peak of the spatial spectrum estimation function is searched, and the spatial coordinate angle corresponding to the searched spectral peak is the spatial orientation angle of the residual interference signal. The spatial orientation angle includes the azimuth angle (i.e., the horizontal angle) and the elevation angle (i.e., the vertical angle).

[0129] The characteristic parameters and spatial azimuth of the residual interference signal are integrated to form a positioning report of the power grid wireless communication interference source;

[0130] The characteristic parameters of the residual interference signal are integrated with the spatial orientation. Combined with the spatial coordinates of the spectrum monitoring equipment itself, the location coordinates of the interference source within the high-voltage substation are calculated. This coordinate calculation method uses triangulation, which uses the position coordinates of the array antenna and the spatial orientation estimated by the multiple signal classification algorithm to calculate the precise location coordinates of the interference source in space through spatial geometric relationships.

[0131] The spatial geometric relationship is the three-dimensional spatial relationship between the position coordinates of the array antenna and the azimuth and elevation angles estimated by the multiple signal classification algorithm;

[0132] Taking the array antenna position coordinates as the origin, the spatial trigonometric function relationship is constructed by combining the azimuth angle and elevation angle;

[0133] The spatial coordinates of the interference source are calculated using the following method:

[0134] Calculate the azimuth distance between the interference source and the array antenna by analyzing the amplitude or time difference of the signal received by the array antenna;

[0135] Using the array antenna position coordinates as the reference point, the 3D spatial coordinates of the interference source are calculated based on the azimuth distance, azimuth angle, and elevation angle using the conversion formula from 3D spherical coordinates to rectangular coordinates (for example, the X coordinate of the rectangular coordinate is the azimuth distance multiplied by the cosine of the elevation angle and then multiplied by the cosine of the azimuth angle; the Y coordinate is the azimuth distance multiplied by the cosine of the elevation angle and then multiplied by the sine of the azimuth angle; and the Z coordinate is the azimuth distance multiplied by the sine of the elevation angle).

[0136] Finally, a power grid wireless communication interference source location report is generated. This report contains information such as the residual interference signal's modulation type, carrier frequency, bandwidth, modulation index, the interference source's three-dimensional spatial coordinates, and detection time, serving as a basis for troubleshooting and managing power grid wireless communication interference sources.

[0137] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0138] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0139] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0140] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0141] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0142] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0143] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0144] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0145] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0146] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A spectrum monitoring and interference analysis method for power grid wireless communication, characterized in that: The steps include: S1: Based on the power frequency magnetic field intensity distribution data of the monitoring point, the eddy current distribution model of the spectrum monitoring equipment is established, and the eddy current distribution parameter set induced by the power frequency magnetic field is output; S2: Collects the spectrum signal of the RF receiving channel of the spectrum monitoring device and the power frequency magnetic flux density signal of the magnetic field sensing channel, and aligns the sampling points using a phase synchronization algorithm; Collect spectrum signals in the RF receiving channel of spectrum monitoring equipment in high-voltage substations; Collect the power frequency magnetic flux density signal in the magnetic field sensing channel of the spectrum monitoring equipment in the high-voltage substation; A phase synchronization algorithm based on a time synchronization reference signal is used to synchronize the spectrum signal collected by the spectrum monitoring equipment's RF receiving channel with the power frequency magnetic flux density signal collected by the magnetic field sensing channel, aligning the sampling points of the spectrum signal and the power frequency magnetic flux density signal. S3: Calculate the high-frequency harmonic frequency characteristics of the secondary radiation generated by the spectrum monitoring equipment under the power frequency magnetic field based on the eddy current distribution parameter set, and generate an eddy current characteristic spectrum line diagram; S4: Based on the spectrum signal, the frequency band energy value that matches the eddy current characteristic spectrum line diagram is extracted, and combined with the power frequency magnetic flux density signal, the pollution ratio of the secondary radiation generated by the spectrum monitoring equipment under the power frequency magnetic field to the spectrum signal is calculated; Perform frequency domain processing on the spectrum signal, and identify the frequency band energy value corresponding to the eddy current characteristic spectrum line diagram in the spectrum signal according to the high-frequency harmonic frequency point characteristics of the eddy current characteristic spectrum line diagram; Calculate the power frequency magnetic flux density change rate of the power frequency magnetic flux density signal of the magnetic field sensing channel; Based on the frequency band energy value and the rate of change of the power frequency magnetic flux density, calculate the pollution ratio of the spectrum signal caused by the secondary radiation of eddy current generated by the spectrum monitoring equipment under the action of the power frequency magnetic field; S5: Based on the pollution ratio, the contamination signal components in the spectrum signal are eliminated and the purified real environment spectrum is output; According to the pollution ratio of the eddy current secondary radiation generated by the spectrum monitoring equipment under the action of the power frequency magnetic field to the spectrum signal, the signal component contaminated by the eddy current secondary radiation corresponding to the eddy current characteristic spectrum line diagram in the spectrum signal is identified; Based on the spectrum filtering method, the signal components contaminated by the secondary radiation of eddy current are removed from the spectrum signal; The spectrum signal after removing the signal components contaminated by the secondary radiation of the eddy current is used as the purified real environment spectrum; S6: Perform a time-frequency joint scan on the purified real environment spectrum to detect the modulation characteristics and spatial orientation of the residual interference signal, and generate a power grid wireless communication interference source location report.

2. The spectrum monitoring and interference analysis method for power grid wireless communication according to claim 1, characterized in that: S1, specifically: Collect power frequency magnetic field intensity distribution data at the monitoring point where spectrum monitoring equipment is installed in high-voltage substations; Based on the structural parameter information of the spectrum monitoring equipment in the high-voltage substation and the power frequency magnetic field intensity distribution data, an eddy current distribution model of the spectrum monitoring equipment under the action of the power frequency magnetic field is established; By analytically solving the electromagnetic induction equation, the eddy current distribution parameter set of the spectrum monitoring equipment in the power frequency magnetic field environment is obtained.

3. The spectrum monitoring and interference analysis method for power grid wireless communication according to claim 2, characterized in that: S3, specifically: Based on the eddy current distribution parameter set and the structural parameters of the spectrum monitoring equipment in the high-voltage substation, the electromagnetic secondary radiation calculation model is used to calculate the high-frequency harmonic frequency characteristics generated by the spectrum monitoring equipment under the action of the power frequency magnetic field; The high-frequency harmonic frequency point characteristics include the high-frequency harmonic frequency value and the corresponding radiation amplitude value; Based on Fourier transform and spectrum analysis methods, an eddy current characteristic spectrum line diagram reflecting the characteristics of high-frequency harmonic frequency points is generated; The horizontal axis of the eddy current characteristic spectrum diagram represents the harmonic frequency, and the vertical axis represents the electromagnetic radiation amplitude value corresponding to the harmonic frequency.

4. The spectrum monitoring and interference analysis method for power grid wireless communication according to claim 3, characterized in that: S6, specifically: Perform joint scanning processing in the time domain and frequency domain on the purified real environment spectrum to obtain the residual interference signal in the real environment spectrum; Modulation recognition is used to extract characteristic parameters of residual interference signals in the real environment spectrum; The spatial orientation of the residual interference signal is determined by using the spatial spectrum estimation method combined with the spatial coordinates of the spectrum monitoring equipment in the high-voltage substation; The characteristic parameters and spatial azimuth of the residual interference signal are integrated to form a positioning report of the power grid wireless communication interference source.

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