Substation grounding grid topology scanning method based on magnetic field distribution

By collecting magnetic induction data of different down conductor combinations and combining waveform recognition and data differentiation processing, fused magnetic field data is generated, which solves the problem of magnetic field interference in the scanning of substation grounding grid topology and improves scanning accuracy and recognition accuracy.

CN120949331BActive Publication Date: 2026-02-10EAST CHINA JIAOTONG UNIVERSITY
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Patent Information

Application Number
CN202511468777.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-10-15
Publication Date
2026-02-10
Estimated Expiration
2045-10-15

AI Technical Summary

Technical Problem

Existing technologies for detecting the topology of substation grounding grids suffer from insufficient scanning accuracy due to magnetic field interference, especially when the position of the down conductor is uncertain, as the magnetic induction intensity components interfere with each other severely, affecting the detection results.

Method used

By collecting magnetic induction data from different down conductor combinations and combining them with different waveform recognition and data differentiation processing, fused magnetic field data is generated, reducing interference caused by co-currents and anti-currents and improving scanning accuracy.

Benefits of technology

This technology improves the accuracy of grounding grid scanning when the location of the down conductor is uncertain, reduces the impact of magnetic field interference on the scanning effect, and enhances the accuracy of identifying the substation grounding grid topology.

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Abstract

The application discloses a substation grounding grid topology scanning method based on magnetic field distribution and belongs to the technical field of power equipment detection. The application respectively collects magnetic induction data of central down lead combination and edge down lead combination, generates first superimposed data and second superimposed data by combining weight superposition, respectively extracts vertical components and parallel components to generate first combination data and second combination data, generates first topology data and second topology data through different waveform identification and data differentiation, generates fusion magnetic field data by combining waveform similarity, and obtains branch topology structure by identifying the center line of the fusion magnetic field data. The application extracts vertical components and parallel components based on different down lead combinations to reduce the interference of other components and improve the accuracy of branch scanning. Meanwhile, the application improves the grounding grid scanning accuracy when the down lead position is uncertain through different differential processing.
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Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of substation grounding, and in particular to a scanning method for substation grounding network topology based on magnetic field distribution. BACKGROUND

[0002] After a long time of use, the substation grounding network may change in topology due to poor welding, soil corrosion, grounding short circuit, etc. Chinese Patent Publication No. CN114924324A discloses a grounding network topology rapid reconstruction method and system. The method acquires an induced magnetic field signal collected by a sensor array vertically arranged above the grounding network conductor, performs derivation processing on the magnetic induction intensity component parallel to the ground of the grounding network conductor, determines the main peak coordinates corresponding to the magnetic induction intensity component, and then locates the grounding network conductor. The application detects the direction of the grounding network branch near the downlead based on the magnetic field differential method, thereby realizing the positioning of the main network conductor of the grounding network without other known branches. The application takes the horizontal component of the magnetic induction intensity as the detection basis, ignoring the magnetic field interference between the conductors. Chinese Patent Publication No. CN112986380B discloses a combined pulse source electromagnetic detection method for grounding network topology. The electromagnetic transmitter of the method injects a bipolar steep pulse current into the grounding network through the grounding downlead, uses a two-component magnetic field receiving coil to combine and collect the horizontal component of the ground pulse magnetic field signal, and then outputs the topology structure image of the grounding network. In order to obtain complete magnetic field information, the grounding downlead selected by the method is the four vertices of the grounding network, and the induced magnetic field directions of the currents of each branch are superimposed on each other. When the relationship between the downlead and the vertex of the grounding network is not clear, the current directions of adjacent branches are partially opposite, and the induced magnetic fields of the branches still interfere with each other, affecting the detection effect of the grounding network. Therefore, the existing technology needs further improvement. SUMMARY

[0003] In order to solve the defects existing in the above-mentioned prior art, the present application proposes a scanning method for substation grounding network topology based on magnetic field distribution, which acquires magnetic induction data through different downlead combinations, and then obtains fused magnetic field data by combining different waveform recognition and data differentiation, thereby improving the scanning accuracy of the grounding network when the position of the downlead is uncertain.

[0004] The technical solution of the present application is as follows:

[0005] The scanning method for substation grounding network topology based on magnetic field distribution comprises the following steps:

[0006] Step 1: At least three groups of reference stations are arranged on the working surface, all downleads of the grounding network are extracted, coordinate data of each downlead is calculated based on the reference stations, distance data of different downlead combinations is calculated, central downlead combinations and edge downlead combinations are extracted based on multiple distance data, and a first weight and a second weight are generated simultaneously.

[0007] Step 2: Extract the center down conductor combination and the edge down conductor combination in sequence. Connect the excitation source between the two sets of down conductors in the down conductor combination. Arrange measuring stations at different measuring points on the working surface in sequence to collect the magnetic induction intensity and coordinate data of the measuring points and generate the magnetic induction data of the working surface.

[0008] Step 3: Repeat Step 2 until the center down conductor combination and the edge down conductor combination are extracted. Generate the first superimposed data based on the magnetic induction data of the center down conductor combination with the first weight, and generate the second superimposed data based on the magnetic induction data of the edge down conductor combination with the second weight.

[0009] Step 4: Extract the modal components of the first superimposed data perpendicular to the working surface to generate the first combined data, and extract the modal components of the second superimposed data parallel to the working surface to generate the second combined data;

[0010] Step 5: Extract the feature waveforms of the first combination data and the second combination data respectively, and calculate the first similarity and the second similarity of the feature waveforms. Perform a first differential process on the feature waveforms of the first combination data to generate the first topological data, and perform a second differential process on the feature waveforms of the second combination data to generate the second topological data.

[0011] Step 6: Based on the first similarity and the second similarity, merge the normalized values ​​of the first topological data and the second topological data to generate fused magnetic field data, and identify the center line of the fused magnetic field data to obtain the branch topology.

[0012] In this invention, in step 1, based on multiple sets of distance data, the n sets of lead wire combinations with the largest distance are extracted sequentially as edge lead wire combinations. The m lead wires contained in these edge lead wire combinations are marked as edge lead wires. The lead wire with the smallest sum of variance of distances to all edge lead wires is found and marked as the center lead wire. The center lead wire is combined with each edge lead wire to generate m sets of center lead wire combinations.

[0013] In this invention, the maximum distance between the center downleader combinations and the edge downleader combinations is extracted respectively, and the weight value ω of each center downleader combination is calculated based on the maximum distance of the center downleader combinations. 1i For i=1,2,…,m, generate the first weight ω1=[ω 11 , ω 12 , …, ω 1m The weight value ω of each edge downline combination is calculated based on the maximum distance of the edge downline combination. 2j For j=1,2,…,n, generate the second weight ω2=[ω 21 , ω 22 , …, ω 2n ].

[0014] In this invention, in step 2, the excitation source is a sinusoidal AC source with a frequency between 300 and 1000 Hz and a current amplitude not exceeding 50 A. A magnetic field coordinate system O'X2Y2Z2 is established with the measurement point as the origin O', and the three-component magnetic induction intensity vector [B] generated by the excitation current at the measurement point is collected. x (t) B y (t) B z (t)],B x (t), B y (t), B z (t) represents the magnetic induction intensity of the measurement point in the X2, Y2, and Z2 directions at time t, respectively. The magnetic induction data of the measurement point is generated by combining the spatial coordinates of the measurement point. The magnetic induction data of all measurement points are summarized to generate the magnetic induction data of the down conductor assembly on the working surface.

[0015] In this invention, in step 3, magnetic induction data in the X2, Y2, and Z2 directions of each measurement point of all center lead-out wire combinations are superimposed based on the first weight to obtain the corresponding center superposition data B. 1x B 1y B 1z Generate the first overlay data S1=[B 1x B 1y B 1z Simultaneously, based on the second weighted superposition of the magnetic induction data of each measurement point in the X2, Y2, and Z2 directions of all edge downlead combinations, the edge superposition data B in the corresponding directions is obtained. 2x B 2y B 2z Generate the second overlay data S2=[B 2x B 2y B 2z ].

[0016] In this invention, in step 4, the magnetic induction data B in the vertical direction of the first superimposed data is extracted. 1z From B 1z Extract the modal components perpendicular to the working surface from any measurement point. The modal components perpendicular to the working surface from each measurement point form the first combined data. Extract the magnetic induction data B in the horizontal direction of the second superimposed data. 2x B 2y From B 2x B 2y The modal components in the X2 and Y2 directions of any measurement point are extracted and then merged to generate modal components parallel to the working surface. The modal components of each measurement point parallel to the working surface form the second set of data.

[0017] In the present application, in step 5, the standard magnetic field shape function of the first combined data and the second combined data is constructed, the characteristic values of each measuring point in the first combined data and the second combined data are extracted and the characteristic waveform is generated by fitting, and the first similarity and the second similarity of the characteristic waveform and the standard magnetic field shape function are calculated respectively.

[0018] In the present application, the first-order differential of the characteristic waveform of the first combined data is calculated to generate the first topological data, the second-order differential of the characteristic waveform of the second combined data is calculated to generate the second topological data, and the normalized values of the first topological data and the second topological data are calculated.

[0019] In the present application, in step 6, the normalized values of the first topological data and the second topological data are weighted and fused based on the first similarity and the second similarity to generate the fused magnetic field data, the magnetic field distribution map is generated based on the fused magnetic field data, the center line of the magnetic field distribution map is identified, and the branch topology structure of the grounding grid is obtained.

[0020] The scanning method for the substation grounding grid topology structure based on the magnetic field distribution of the present application has the following beneficial effects: the present application respectively collects the magnetic induction data of the central down conductor combination and the edge down conductor combination, extracts the vertical component and the parallel component, combines different waveform recognition and data differentiation to obtain the fused magnetic field data and the branch topology structure. The central down conductor combination can reduce the interference of the parallel component caused by the same current, and the edge down conductor combination can reduce the interference of the vertical component caused by the opposite current. Further, the present application adopts different differential processing methods for the numerical characteristics of the vertical component and the parallel component, thereby improving the accuracy of the branch scanning. The present application adjusts the weight of the data superposition in combination with the weight adjustment of the different down conductor combinations, and simultaneously combines the feature waveform to determine the weight of the data fusion, thereby improving the scanning accuracy of the grounding grid when the down conductor position is uncertain. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 It is a schematic diagram of a substation with down conductor;

[0022] Figure 2 It is a schematic diagram of the equivalent circuit of the grounding grid of the present application;

[0023] Figure 3 It is a flowchart of the scanning method for the substation grounding grid topology structure based on the magnetic field distribution of the present application;

[0024] Figure 4 It is a schematic diagram of the substation grounding grid of the present application;

[0025] Figure 5 It is a schematic diagram of the arrangement of the reference station and the measuring station of the present application;

[0026] Figure 6 It is a distance schematic diagram of different down conductor combinations of the present application;

[0027] Figure 7 The current diagram of the combined connection of the excitation source by the central down lead of the application;

[0028] Figure 8 The current diagram of the combined connection of the excitation source by the edge down lead of the application;

[0029] Figure 9 The diagram of measuring the electromagnetic induction intensity of the application;

[0030] Figure 10 The diagram of measuring the point coordinate system of the application;

[0031] Figure 11 The curve diagram of the first combined data and the first topology data of the application;

[0032] Figure 12 The curve diagram of the second combined data and the second topology data of the application;

[0033] Figure 13 The equivalent circuit diagram of the measuring station of the application.

[0034] The reference signs in the drawings: power transformation equipment 100, soil layer 200, grounding net 300, branch 311, node 312, down lead 400, reference station 500, measuring station 600. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is described and explained below in combination with the drawings and examples.

[0036] As Figure 1 and Figure 2As shown, the transformer substation has multiple groups of transformer equipment 100, and the grounding grid 300 of the transformer substation is buried in the soil layer 200, the grounding grid 300 has multiple branches 311, different branches are connected to each other through nodes 312, and part of the nodes are connected to the transformer equipment 100 through the downlead 400. The grounding current of the transformer equipment 100 enters the grounding grid 300 through the downlead 400, and is scattered into the soil layer 200 after passing through other nodes and branches. When detecting the grounding grid topology, the branches 311 of the grounding grid are equivalent to resistors, the measuring station 600 is equivalent to a current injection end, and the soil layer 200 is regarded as an insulator. When the relationship between the downlead and the node of the grounding grid is not clear, the current directions of adjacent branches are partially opposite and partially the same, when the current directions of adjacent branches are mostly the same, the magnetic induction intensity in the vertical direction is offset, and when the current directions of adjacent branches are mostly opposite, the magnetic induction intensity in the horizontal direction is offset. The induced magnetic fields of the branches interfere with each other, affecting the detection effect of the grounding grid. Therefore, the present application provides a scanning method for the grounding grid topology of a transformer substation based on magnetic field distribution, which distinguishes different types of downlead combinations to extract magnetic induction data in different directions, and then combines different waveform recognition and data differentiation to obtain fused magnetic field data, thereby improving the scanning accuracy of the grounding grid when the position of the downlead is uncertain. Embodiment one

[0037] As Figures 3 to 13 The scanning method for the grounding grid topology of a transformer substation based on magnetic field distribution provided by the present application comprises the following steps:

[0038] Step 1: At least three groups of reference stations are arranged on the working surface, all downleads of the grounding grid are extracted, coordinate data of each downlead is calculated based on the reference stations, distance data of different downlead combinations is calculated, central downlead combinations and edge downlead combinations are extracted based on multiple sets of distance data, and first and second weights are generated. In this embodiment, a grid can be established on the working surface to determine the relative positions of the reference stations. A preferred method for establishing a grounding grid simulation grid measurement model on the working surface is as follows: first, the general trend of the grounding grid conductor is determined by the circumferential method, and the trend and range of the grid are determined based on this; second, a rectangular grid measurement model with C rows and R columns is established on the working surface, the working surface is divided into (C-1)(R-1) regular unit cells, the grid spacing is d0, each horizontal line of the grid is set as an observation line, and the intersection of the rows and columns of the grid is set as a measurement point.

[0039] A right-handed Cartesian coordinate system OX1Y1Z1 is established with the lower left corner vertex of the grid as the origin O. This coordinate system serves as a reference coordinate system for calibrating the positions of the down conductors and measurement points. The working surface is a plane parallel to the horizontal plane OX1Y1 in the reference coordinate system. The X1 and Y1 axes are parallel to the rows and columns of the grid, respectively, and the Z1 axis is perpendicular to the working surface and points upwards. The coordinates of the reference station are calibrated according to the reference coordinate system. All down conductors of the grounding grid are extracted, and the coordinates of each down conductor are calculated based on the reference station coordinates to generate the coordinate data of the down conductors. Figure 6 Based on the coordinates of the downleaders, the distance between different downleaders is calculated, generating multiple sets of distance data for different combinations of downleaders.

[0040] Based on multiple sets of distance data, the n groups of drop line combinations with the largest distances are sequentially extracted as edge drop line combinations. The m drop lines contained in these edge drop line combinations are marked as edge drop lines. The drop line with the smallest sum of variances of distances to all edge drop lines is marked as the center drop line. The center drop line is then combined with each edge drop line combination to generate m groups of center drop line combinations. Further, the maximum distance between the center drop line combinations and the edge drop line combinations is extracted separately. Based on the maximum distance of the center drop line combinations, the weight value ω of each center drop line combination is calculated. 1i For i=1,2,…,m, generate the first weight ω1=[ω 11 , ω 12 , …, ω 1m The weight value ω of each edge downline combination is calculated based on the maximum distance of the edge downline combination. 2j For j=1,2,…,n, generate the second weight ω2=[ω 21 , ω 22 , …, ω 2n ].

[0041] Step 2: Sequentially extract the center down conductor assembly and the edge down conductor assembly. Connect an excitation source between the two sets of down conductors in each assembly. Arrange measuring stations at different measurement points on the working surface, collect the magnetic induction intensity and coordinate data of the measuring stations, and generate the magnetic induction data of the working surface. The excitation source is a sinusoidal AC source with a frequency between 300 and 1000 Hz and a current amplitude not exceeding 50 A.

[0042] Specifically, in order to better acquire the induced magnetic field signal and reduce the interference of the substation's ambient magnetic field, this embodiment uses a sinusoidal AC source with a frequency of 1kHz and an amplitude of 1A as the excitation source. For example... Figure 4An excitation source is connected in series with a galvanometer and in parallel with a voltmeter. The center down conductor combination and the edge down conductor combination are extracted sequentially. The excitation source is connected to the two sets of down conductors in the selected down conductor combination, causing a sinusoidal current of a specific frequency to flow into the grounding grid conductor. According to the Biot-Savart law, this current will induce a magnetic field in the space around the conductor, such as... Figure 9 As shown. The measuring station is moved sequentially to each measuring point, and a magnetic field coordinate system O'X2Y2Z2 is established with the measuring point as the origin O'. This system is used to calibrate the magnetic field direction. The X2, Y2, and Z2 axes are parallel to the X1, Y1, and Z1 axes of the reference coordinate system, respectively. Figure 10 As shown. The three-component magnetic induction vector [B] generated by the excitation current at the measurement point is collected. x (t) B y (t) B z (t)],B x (t), B y (t), B z (t) represents the magnetic induction intensity of the measurement point in the X2, Y2, and Z2 directions at time t, respectively. The magnetic induction data of the measurement point is generated by combining the spatial coordinates of the measurement point. The magnetic induction data of all measurement points are summarized to generate the magnetic induction data of the down conductor assembly on the working surface.

[0043] like Figure 13 The measuring station in this embodiment includes three sets of mutually perpendicular induction coils. According to the right-hand rule, the induced magnetic field of the grounding grid lies in a magnetic field plane perpendicular to the branch direction. The magnetic field component is calculated based on the induced voltage of each induction coil, and the three sets of magnetic field components are mutually perpendicular. The magnetic induction intensity at the measuring point is obtained based on the three sets of magnetic field components. This method can reduce the influence of magnetic fields in other branch directions. Further, the induction coil is equivalent to an RLC equivalent circuit composed of its own distributed capacitance, coil resistance, and parasitic inductance. The magnetic field induces an electromotive force in the induction coil, and the induced electromotive force is proportional to the magnetic induction intensity. The measuring station also includes a signal acquisition unit and a signal analysis unit connected to the induction coils. The signal acquisition unit acquires the induced electromotive force of the induction coils, and the signal analysis unit calculates the magnetic induction intensity based on the induced electromotive force of the three induction coils.

[0044] Step 3: Repeat Step 2 until the center downlead combination and edge downlead combination are extracted. Generate the first superimposed data based on the magnetic induction data of the center downlead combination using the first weight, and generate the second superimposed data based on the magnetic induction data of the edge downlead combination using the second weight. Specifically, superimpose the magnetic induction data of each measurement point of all center downlead combinations in the X2, Y2, and Z2 directions using the first weight to obtain the corresponding center superimposed data B. 1x B 1y B 1z Generate the first overlay data S1=[B 1x B 1yB 1z Simultaneously, based on the second weighted superposition of the magnetic induction data of each measurement point in the X2, Y2, and Z2 directions of all edge downlead combinations, the edge superposition data B in the corresponding directions is obtained. 2x B 2y B 2z Generate the second overlay data S2=[B 2x B 2y B 2z ].

[0045] Step 4: After extracting the modal components perpendicular to the working surface from the first superimposed data, generate the first combined data; after extracting the modal components parallel to the working surface from the second superimposed data, generate the second combined data. Specifically, extract the magnetic induction data B in the direction perpendicular to the first superimposed data. 1z From B 1z Extract the modal components perpendicular to the working surface from any measurement point. The modal components perpendicular to the working surface from each measurement point form the first combined data. Extract the magnetic induction data B in the horizontal direction of the second superimposed data. 2x B 2y From B 2x B 2y The modal components in the X2 and Y2 directions of any measurement point are extracted and then merged to generate modal components parallel to the working surface. The modal components of each measurement point parallel to the working surface form the second set of data.

[0046] Step 5: Extract the feature waveforms of the first and second combined data respectively, and calculate the first and second similarities of the feature waveforms. Perform a first differential operation on the feature waveforms of the first combined data to generate the first topological data, and perform a second differential operation on the feature waveforms of the second combined data to generate the second topological data. Specifically, construct the standard magnetic field shape function of the first and second combined data, extract the feature values ​​of each measurement point in the first and second combined data, and fit them to generate feature waveforms. Calculate the first and second similarities between the feature waveforms and the standard magnetic field shape function respectively. Further, calculate the first derivative of the feature waveforms of the first combined data to generate the first topological data, calculate the second derivative of the feature waveforms of the second combined data to generate the second topological data, and calculate the normalized values ​​of the first and second topological data. The value range can be set to [-1, 1].

[0047] Step 6: Based on the first similarity and the second similarity, the normalized values ​​of the first and second topological data are merged to generate fused magnetic field data. The centerline of the fused magnetic field data is identified to obtain the branch topology. Specifically, the normalized values ​​of the first and second topological data are weighted and merged based on the first similarity and the second similarity to generate fused magnetic field data. The normalized value of the fused magnetic field data is calculated, and the normalized value range is [0, 255]. Example 4 further discloses a preferred method for generating fused magnetic field data and calculating its normalized value. The preferred method for obtaining the branch topology in this example is described below.

[0048] The purpose of this invention is to determine the grounding grid topology, thus the vertical coordinates (Z1 axis coordinates) of the measurement points can be ignored. Considering only the horizontal coordinates (X1 and Y1 axis coordinates) of the measurement points, the normalized values ​​of each measurement point in the fused magnetic field data are mapped onto a two-dimensional grid to generate an OX1Y1 magnetic field distribution map.

[0049] The distribution map is then binarized based on a threshold (e.g., pixel values ​​from 10 to 50). Values ​​below the threshold are defined as background areas and their pixel values ​​are set to 0 (black). Values ​​in the grid that are higher than or equal to the threshold are defined as conductor areas and their pixel values ​​are set to 1 (white). This enhances the contrast between conductor areas and the background, highlighting the bright stripe areas of the corresponding conductors.

[0050] Furthermore, morphological processing is performed on the binarized image. Based on the opening operation (erosion followed by dilation) in morphology, noise points and smooth strip edges in the binarized image are removed. Then, the erosion operation is iteratively performed to transform the smooth strips into single-pixel widths to extract the centerline, while preserving its original topology (connectivity and intersections remain unchanged). The intersections of the centerlines are identified and set as nodes of the branches. By tracing the centerline paths between nodes, the complete branch topology of the grounding grid can be reconstructed. Example 2

[0051] This embodiment further discloses preferred methods for calculating the coordinates of the downleads, generating the combination of center downleads and the combination of edge downleads, and generating the first weight and the second weight.

[0052] First, calculate the coordinates of the leader line. For example... Figure 5 In this embodiment, four reference stations 500 are set up, and the reference station marker point A is calibrated based on the reference coordinate system. k The coordinates of A k (a k ,b k ,c k ), a k b k c k They are A kThe coordinates of the downleader point G and the reference station point A are given in the X, Y, and Z axes, with k = 1, 2, 3, 4. k slope distance s k Vertical angle θ k and horizontal angle α k Where, the vertical angle θ k For A k The angle between line G and the vertical plane, and the horizontal angle α. k For A k The line G is mapped to the angle θ between the horizontal plane and the X1 axis. k and α k The range is [0°, 90°], combined with A k The reference coordinates of G are used to calculate the coordinates of G. k (x k ,y k ,z k ), x k =a k +s k ·sin(θ k )·cos(α k ), y k =b k +s k ·sin(θ k )·sin(α k ), z k =c k +s k ·cos(θ k ), the reference coordinates G obtained from solving all reference stations k Take the arithmetic mean as the coordinates of the leader line.

[0053] Then, generate the center downleader combination and the edge downleader combination. Calculate the Euclidean distance between all pairs of downleaders, and select the n downleader combinations with the largest distances as the edge downleader combinations. Mark all m downleaders contained in these combinations as edge downleaders, denoted as set E={E1, E2, ..., E...}. m Iterate through the other downlines not marked as edge downlines as candidate points, and calculate the distances d1, d2, ..., d from each candidate point to all edge downlines in set E. m Calculate the variance of this set of distance values, mark the candidate point with the smallest distance variance as the center downline S, and connect the center downline S with each edge downline E. i Combine to generate m groups of center lead-out wire combinations SE i , i=1,2,…,m.

[0054] Regenerate the first and second weights. Extract the maximum distance d of the center lead-down line combination.max According to the distance d of each group of center down conductor combinations SEi Calculate its weight value ω 1i ω 1i =d SEi / d max The greater the distance between the lead-in line combinations, the greater their weight value. The first weight ω1 is generated based on the weight value of the center lead-in line combination. 11 , ω 12 , …, ω 1m Extract the maximum distance of the edge downleader combinations, and use the same method to obtain the weight values ​​ω for different edge downleader combinations. 2j For j=1,2,…,n, generate the second weight ω2=[ω 21 , ω 22 , …, ω 2n ]. Example 3

[0055] This embodiment further discloses a preferred method for generating the first and second combined data according to the present invention. In a simpler embodiment, the present invention can also directly extract the projection components of the corresponding directions as modal components from the magnetic induction data.

[0056] Extract magnetic induction data B in the vertical direction of the first superimposed data. 1z From B 1z Extract the magnetic induction data B in the Z2 direction of the measurement point P. 1z,p (t), which is decomposed into K modal components {P1(t), P2(t), ..., P} based on the variational mode decomposition (VMD) algorithm. K (t)} and the corresponding center frequencies {f1,f2,…,f K In a specific embodiment, the number of modes K can be preset to 4 based on the excitation source frequency and the number of major interfering harmonics, and the penalty factor α can be set to 2000 to obtain a suitable modal bandwidth. The center frequency f of each modal component is then used as the basis for determining the modal bandwidth. k Match the modal component P closest to the excitation source frequency f0 λ (t), This is taken as the effective target magnetic field signal separated from the background noise at measurement point P, and denoted as the modal component perpendicular to the working surface at that measurement point. The vertical modal components of all measurement points are combined to generate the first combined data.

[0057] Extract the horizontal magnetic induction data B from the second superimposed data. 2x B 2y From B respectively 2x and B 2y Extract the magnetic induction data B in the X2 and Y2 directions of the measurement point Q. 2x,Q(t), B 2y,Q (t), the modal component Q in the horizontal X2 direction of the measurement point Q can be obtained by the same method. x (t) and the modal component Q in the horizontal Y2 direction y (t), combining the modal components in the X2 and Y2 directions yields the modal component Q of the measurement point Q parallel to the working surface. xy (t), The second set of combined data is generated by integrating the horizontal modal components of all measurement points. Example 4

[0058] This embodiment further discloses a preferred method for generating fused magnetic field data according to the present invention.

[0059] In this embodiment, the grid spacing d0 is set to 5m, then there are C observation lines y1=0, y2=5, ..., y C =(C-1)×5. Extract the first or second combination of data for each observation line as the analysis object.

[0060] The standard magnetic field shape function in the vertical direction. Construct the standard magnetic field shape function F1(x) in the vertical direction as the ideal function of the first combined data characteristic waveform. According to the principle of magnetic induction, ideally, F1(x) = (A1·|x-b1|) / [h 2 +(x-b1) 2 Where A1 is a characteristic parameter reflecting the permeability of the spatial magnetic field and the magnitude of the excitation current, b1 is the center position of the characteristic waveform, and h is the burial depth of the grounding grid. Extract the observation line y from the first set of data. i The characteristic values ​​of the magnetic induction data at the corresponding measurement points are used to fit and form the characteristic waveform f of the observation line. 1,yi (x), i=1,2,…,C, where x is the coordinate of the measurement point on the X1 axis.

[0061] Generate the first similarity score. Calculate the observed line y. i Characteristic waveform f 1,yi The peak similarity M between (x) and the standard magnetic field shape function F1(x) ni and shape similarity M si After merging, the comprehensive similarity M of the observation line is generated. 1i . Where N is the number of peaks, x k x k 'respectively functions f 1,yi The X1-axis coordinates corresponding to the k-th peak of F1(x) and F1(x), f 1,yi (x k ) is x k corresponding f 1,yi The peak value of F1(x)k ') is x k The peak size of the corresponding F1(x). β is a scaling factor used to control the magnitude of peak similarity, with a value range of (0,1]. The larger the β, the smaller the peak similarity. M 1i =μ·M ni +(1-μ)·|M si |μ is a weighting factor used to adjust the proportion of peak similarity and shape similarity in the overall similarity score. Its value ranges from [0,1], with an initial value of 0.5. A first similarity score M1 is generated based on the overall similarity of all observed lines, M1=[M... 11 M 12 ,…,M 1C In a more preferred embodiment, the shape similarity of the waveform curves can also be calculated by integration.

[0062] The standard magnetic field shape function in the horizontal direction. The standard magnetic field shape function F2(x) in the horizontal direction is constructed as an ideal function of the second combined data characteristic waveform. According to the principle of magnetic induction, ideally, F2(x) = (A2·h) / [h] 2 +(x-b2) 2 A2 represents the characteristic parameters reflecting the permeability of the spatial magnetic field and the magnitude of the excitation current; b2 is the center position of the characteristic waveform; and h is the burial depth of the grounding grid. Extract the observation line y from the second set of data. i Characteristic waveform f 2,yi (x), i=1,2,…,C, where x is the coordinate of the measurement point on the X1 axis.

[0063] Generate a second similarity. Calculate the feature waveform f using the same method. 2,yi The combined similarity M between (x) and the standard magnetic field shape function F2(x) 2i Generate a second similarity M2, M2=[M 21 M 22 ,…,M 2C ].

[0064] Generate the first topological data. Calculate the observed line y in the first combined data. i Characteristic waveform f 1,yi The first differential of (x) Abandon small components of the sine wave. Where μ is the magnetic permeability of the soil, I is the current amplitude, and h is the burial depth of the grounding grid. The first-order differential curve... As the observation line y i The first topological data curve from which the observation line y is extracted. iThe amplitude values ​​of all measurement points are combined with the amplitude values ​​of all observation lines, and then combined with the spatial coordinates of the measurement points to generate the first topological data W1, where W1 is a C×R matrix. For example... Figure 11 As shown, the first combination data curve has a double main peak distribution, while the first topological data curve obtained by first-order differentiation has a single main peak distribution. The peak point of the single main peak corresponds to the zero point of the first combination data curve. Therefore, first-order differentiation can transform the zero-crossing features that are not easy to identify in the first combination data into the extreme point features that are easier to detect, making the feature point positions easier to identify.

[0065] Generate the second topology data. Calculate the observation line y in the second combined data. i Characteristic waveform f 2,yi The second derivative of (x) Abandon small components of the sine wave. Where μ is the magnetic permeability of the soil, I is the current amplitude, and h is the burial depth of the grounding grid. The second-order differential curve... As the observation line y i The second topological data curve from which the observation line y is extracted. i The amplitude set of all measurement points, combined with the amplitude set of all observation lines, and combined with the spatial coordinates of the measurement points, generates the second topological data W2, where W2 is a C×R matrix. For example... Figure 12 As shown, the second combined data curve exhibits a positive main peak, while the second topological data curve obtained through second-order differentiation shows a negative main peak. The comparison reveals that the main peak width of the second topological data curve is significantly narrower than that of the second combined data curve, and the peak shape is steeper. Therefore, first-order differentiation processing makes the magnetic field characteristics of the second combined data more pronounced, which is beneficial for the subsequent accurate identification of the grounding grid topology.

[0066] Calculate the normalized values ​​of the first and second topological data. The normalized value W of the first topological data. 1n =(W1-W 1,min ) / (W 1,max -W 1,min ), W 1,max and W 1,min These represent the maximum and minimum values ​​of the first topological data, respectively. Since the second topological data generated by the second derivative is negative, we first need to calculate the inverse of the second topological data to obtain W2', and then use the same method to calculate the normalized value of W2' to obtain the normalized value W of the second topological data. 2n .

[0067] Generate fused magnetic field data. Based on the first and second similarity scores, merge the normalized values ​​of the first and second topological data to generate fused magnetic field data W. all W all W is a C×R matrix. all(u,v)=M 1u ·W 1n (u,v)+M 2u ·W 2n (u,v), where u and v are matrices W. all The row and column indices are given, u∈{1,2,…,C}, v∈{1,2,…,R}. Further, the fused magnetic field data is normalized to prepare for accurate mapping to the image grayscale range. The normalized fused magnetic field data W... all =255×(W) all -W all,min ) / (W all,max -W all,min ), W all,max and W all,min These represent the maximum and minimum values ​​of the fused magnetic field data, respectively. To visualize the fused magnetic field data, the normalized fused magnetic field data range is [0, 255].

[0068] 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 and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A scanning method for the substation grounding grid topology based on magnetic field distribution, characterized in that, Includes the following steps: Step 1: Deploy at least three sets of reference stations on the work surface, extract all the down conductors of the grounding grid, calculate the coordinate data of each down conductor based on the reference stations, calculate the distance data of different down conductor combinations, extract the center down conductor combination and the edge down conductor combination based on multiple sets of distance data, and generate the first weight and the second weight at the same time. Step 2: Extract the center down conductor combination and the edge down conductor combination in sequence. Connect the excitation source between the two sets of down conductors in the down conductor combination. Arrange measuring stations at different measuring points on the working surface in sequence to collect the magnetic induction intensity and coordinate data of the measuring points and generate the magnetic induction data of the working surface. Step 3: Repeat Step 2 until the center down conductor combination and the edge down conductor combination are extracted. Generate the first superimposed data based on the magnetic induction data of the center down conductor combination with the first weight, and generate the second superimposed data based on the magnetic induction data of the edge down conductor combination with the second weight. Step 4: Extract the modal components of the first superimposed data perpendicular to the working surface to generate the first combined data, and extract the modal components of the second superimposed data parallel to the working surface to generate the second combined data; Step 5: Extract the feature waveforms of the first combination data and the second combination data respectively, and calculate the first similarity and the second similarity of the feature waveforms. Perform a first differential process on the feature waveforms of the first combination data to generate the first topological data, and perform a second differential process on the feature waveforms of the second combination data to generate the second topological data. Step 6: Based on the first similarity and the second similarity, merge the normalized values ​​of the first topological data and the second topological data to generate fused magnetic field data, and identify the center line of the fused magnetic field data to obtain the branch topology.

2. The scanning method for substation grounding grid topology based on magnetic field distribution according to claim 1, characterized in that, In step 1, based on multiple sets of distance data, the n sets of lead wire combinations with the largest distance are extracted sequentially as edge lead wire combinations. The m lead wires contained in these edge lead wire combinations are marked as edge lead wires. The lead wire with the smallest sum of variance of distances to all edge lead wires is found and marked as the center lead wire. The center lead wire is combined with each edge lead wire to generate m sets of center lead wire combinations.

3. The scanning method for the substation grounding grid topology based on magnetic field distribution according to claim 2, characterized in that, Extract the maximum distance from the center downline combination and the edge downline combination respectively, and calculate the weight value ω of each center downline combination based on the maximum distance of the center downline combination. 1i For i=1,2,…,m, generate the first weight ω1=[ω 11 ,ω 12 , …, ω 1m The weight value ω of each edge downline combination is calculated based on the maximum distance of the edge downline combination. 2j For j=1,2,…,n, generate the second weight ω2=[ω 21 , ω 22 , …, ω 2n ].

4. The scanning method for substation grounding grid topology based on magnetic field distribution according to claim 1, characterized in that, In step 2, the excitation source is a sinusoidal AC source with a frequency between 300 and 1000 Hz and a current amplitude not exceeding 50 A. A magnetic field coordinate system O'X2Y2Z2 is established with the measurement point as the origin O', and the three-component magnetic induction intensity vector [B] generated by the excitation current at the measurement point is collected. x (t) B y (t) B z (t)],B x (t), B y (t), B z (t) represents the magnetic induction intensity of the measurement point in the X2, Y2, and Z2 directions at time t, respectively. The magnetic induction data of the measurement point is generated by combining the spatial coordinates of the measurement point. The magnetic induction data of all measurement points are summarized to generate the magnetic induction data of the down conductor assembly on the working surface.

5. The scanning method for substation grounding grid topology based on magnetic field distribution according to claim 4, characterized in that, In step 3, based on the first weighted superposition of the magnetic induction data of each measurement point in the X2, Y2, and Z2 directions of all center lead-down wire combinations, the corresponding center superposition data B is obtained. 1x B 1y B 1z Generate the first overlay data S1=[B 1x B 1y B 1z Simultaneously, based on the second weighted superposition of the magnetic induction data of each measurement point in the X2, Y2, and Z2 directions of all edge downlead combinations, the edge superposition data B in the corresponding directions is obtained. 2x B 2y B 2z Generate the second superimposed data S2=[B 2x B 2y B 2z ].

6. The scanning method for substation grounding grid topology based on magnetic field distribution according to claim 5, characterized in that, In step 4, the magnetic induction data B in the vertical direction of the first superimposed data is extracted. 1z From B 1z Extract the modal components perpendicular to the working surface from any measurement point. The modal components perpendicular to the working surface from each measurement point form the first combined data. Extract the magnetic induction data B in the horizontal direction of the second superimposed data. 2x B 2y From B 2x B 2y The modal components in the X2 and Y2 directions of any measurement point are extracted and then merged to generate modal components parallel to the working surface. The modal components of each measurement point parallel to the working surface form the second set of data.

7. The scanning method for substation grounding grid topology based on magnetic field distribution according to claim 1, characterized in that, In step 5, a standard magnetic field shape function is constructed for the first and second combined data. Feature values ​​of each measurement point in the first and second combined data are extracted and fitted to generate a feature waveform. The first similarity and the second similarity between the feature waveform and the standard magnetic field shape function are calculated respectively.

8. The scanning method for substation grounding grid topology based on magnetic field distribution according to claim 7, characterized in that, Calculate the first derivative of the characteristic waveform of the first combined data to generate the first topological data, calculate the second derivative of the characteristic waveform of the second combined data to generate the second topological data, and calculate the normalized value of the first topological data and the second topological data.

9. The scanning method for substation grounding grid topology based on magnetic field distribution according to claim 1, characterized in that, In step 6, the normalized values ​​of the first and second topological data are weighted and fused based on the first and second similarity to generate fused magnetic field data. A magnetic field distribution map is generated based on the fused magnetic field data, the center line of the magnetic field distribution map is identified, and the branch topology of the grounding grid is obtained.

Citation Information

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