Grounding grid topology identification method based on key feature point detection of magnetic response data
By using a key feature point detection method based on magnetic response data and employing the local maximum method to identify the topology of the grounding grid, the problem of slow identification process and high misjudgment rate in the existing technology is solved, and efficient and accurate grounding grid topology identification is achieved.
Patent Information
- Application Number
- CN202211136625.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-09-19
- Publication Date
- 2025-11-04
- Estimated Expiration
- 2042-09-19
AI Technical Summary
Existing grounding grid topology identification methods suffer from slow identification processes, high false positive rates, complex algorithms, and large computational loads. In particular, when the grounding grid drawing data is incomplete or differs significantly from the design drawing, it is difficult to efficiently and accurately identify the topology of the grounding grid.
After acquiring and preprocessing the magnetic response data of the grounding grid, key feature points, including two-dimensional and one-dimensional local maxima, are detected using the local maximum method. The topology of the grounding grid is then drawn by combining the feature point detection method of the magnetic response data.
It improves the efficiency and accuracy of grounding grid topology identification, simplifies the algorithm, reduces the amount of computation, and can accurately identify the topology of the grounding grid without power outages or excavation.
Smart Images
Figure CN115496915B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of grounding grid topology detection, and in particular to a grounding grid topology identification method based on magnetic response data key feature point detection. BACKGROUND
[0002] The grounding grid is an important foundation for ensuring the safe operation of a substation. Therefore, in order to reduce the probability of substation accidents caused by grounding grid corrosion, it is necessary to regularly troubleshoot and replace the grounding grid conductors.
[0003] When diagnosing the fault of the grounding network of an old substation, it is often found that the drawing data of the grounding grid is incomplete or has a large difference from the design drawing. Through the method of large-area excavation and troubleshooting, not only is the workload large, the target is unclear, and resources are wasted, but also the safe operation of the power system is affected, which completely cannot meet the needs of modern development. Therefore, the power system needs a convenient method to verify the topology structure of the grounding grid. Realize the checking of the underground grounding grid from the ground by the equipment without power off and excavation. According to the collected data, the position of the grounding grid flat steel is located through data mining, so that the staff can real-time understand the condition of the underground grounding grid, so as to timely find out hidden dangers and provide a reliable theoretical basis for grounding grid maintenance work.
[0004] The existing technical solutions often use morphological filtering, edge detection, induced voltage differential method, etc. to obtain the grounding grid topology structure. These methods need to perform a large number of operations on the data. At the same time, the use of induced voltage differential will amplify the noise in the original image, and the data preprocessing requirement is high; for grounding grids in different situations, the morphological filtering method needs to find a suitable structure element as the kernel. Therefore, these methods have the disadvantages of complex algorithm and large amount of calculation.
[0005] In addition, the commonly used grounding grid topology structure acquisition method also has the following problems: an electric current is introduced into the grounding grid down lead, the magnetic response data collected in the horizontal direction on the ground surface is drawn into a heat map, and then the underground grounding grid topology structure is manually drawn by the detection personnel. However, in actual engineering, the network structure of the grounding grid will shunt the electric current, causing weak local current, and the change trend of the ground surface magnetic data caused by the local current is not obvious, so the detection personnel is easy to miss the measurement, and the position of the flat steel is not accurate and the efficiency is low.
[0006] Therefore, the existing grounding grid topology identification has the technical problems of long identification process, high misjudgment rate, and complex algorithm, which need to be solved urgently. SUMMARY
[0007] The technical problem solved by the present application is that when a person obtains the grounding grid topology structure through the magnetic response data of the grounding grid, the identification process is slow and the misjudgment is high. According to the trend of the magnetic response data of the current-carrying flat steel on the ground with the change of the position, the present application provides a grounding grid topology identification method based on key feature point detection of magnetic response data. The method uses the characteristics that the magnetic response data of the current-carrying flat steel in the vertical and horizontal directions and the magnetic response data of the crossing flat steel at the crossing position have local maximum values as key feature points, and draws the grounding grid topology structure.
[0008] According to one aspect of the present application, a grounding grid topology identification method based on key feature point detection of magnetic response data comprises the following steps:
[0009] Obtain the original magnetic response data of the grounding grid.
[0010] Preprocess the original magnetic response data to obtain the preprocessed magnetic response data.
[0011] Based on the preprocessed magnetic response data, perform key feature point detection, specifically including:
[0012] Using the local maximum value method, perform two-dimensional local maximum value selection on the two-dimensional matrix formed by the preprocessed magnetic response data, and the obtained two-dimensional local maximum value point set is the position point set of the underground flat steel intersection point.
[0013] Perform one-dimensional local maximum value selection on each row of the two-dimensional matrix, and then perform one-dimensional local maximum value selection on each column, and the obtained one-dimensional local maximum value point set is the position point set of the underground flat steel.
[0014] Integrate the underground flat steel intersection point set and the underground flat steel position point set to obtain the data matrix of the position information of the grounding grid topology structure.
[0015] Further, the preprocessing of the original magnetic response data includes data normalization and data interpolation processing.
[0016] Preferably, the data normalization adopts maximum value normalization, taking the maximum value of the data as 1 and the minimum value of the data as 0, and the rest of the data is proportionally corresponding to the value between 0 and 1.
[0017] Preferably, the data interpolation processing adopts a bicubic interpolation algorithm, selects the nearest 16 points around the point to be interpolated, performs weighted average on the 16 points with the weight of each point, and takes the weighted average result as the value of the point to be interpolated, wherein the weight of each point is determined by the horizontal distance and the vertical distance from the point to the point to be interpolated.
[0018] Preferably, the local maximum value method is used to perform two-dimensional local maximum value selection on the two-dimensional matrix formed by the preprocessed magnetic response data, including:
[0019] The four-neighborhood maximum value or eight-neighborhood local maximum value of the two-dimensional matrix is selected; the four-neighborhood maximum value means that the value is greater than or equal to the value of each point on a four-connected region, and the eight-neighborhood maximum value means that the value is greater than or equal to the value of each point on an eight-connected region.
[0020] Preferably, the positions in the two-dimensional matrix that meet the two-dimensional local maximum value condition are assigned a value of 1, and the remaining positions are assigned a value of 0.
[0021] Preferably, the positions in each row and each column of the two-dimensional matrix that meet the one-dimensional local maximum value condition are assigned a value of 1, and the remaining positions are assigned a value of 0.
[0022] According to a second aspect of the present application, a ground grid topology identification device based on key feature point detection of magnetic response data comprises the following modules:
[0023] A data acquisition module is configured to acquire original magnetic response data of a ground grid.
[0024] A preprocessing module is configured to preprocess the original magnetic response data to obtain preprocessed magnetic response data.
[0025] A key feature point detection module is configured to detect key feature points based on the preprocessed magnetic response data, and specifically configured to:
[0026] A local maximum value method is used to select two-dimensional local maximum values from a two-dimensional matrix formed by the preprocessed magnetic response data, and a two-dimensional local maximum value point set obtained by the selection is a point set of underground flat steel intersection points.
[0027] One-dimensional local maximum values are selected from each row of the two-dimensional matrix, and one-dimensional local maximum values are further selected from each column, and a one-dimensional local maximum value point set obtained by the selection is a point set of underground flat steel positions.
[0028] A topology structure identification module is configured to integrate the point set of underground flat steel intersection points and the point set of underground flat steel positions to obtain a data matrix of ground grid topology structure position information.
[0029] According to a third aspect of the present application, an electronic device comprises a memory and a processor, and a computer program is stored on the memory, and when the computer program is executed by the processor, the steps of the ground grid topology identification method are executed.
[0030] According to a fourth aspect of the present application, a non-transitory computer readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the ground grid topology identification method are implemented.
[0031] The technical scheme provided by the application has the following beneficial effects: the application provides a grounding grid topology identification method and device based on magnetic response data key feature point detection, equipment and storage medium, the original magnetic response data of the grounding grid is obtained, the magnetic response data is preprocessed, key feature point detection is performed based on the preprocessed magnetic response data, specifically including: a two-dimensional local maximum value selection is performed on a two-dimensional matrix formed by the magnetic response data by using a local maximum value method, and a two-dimensional local maximum value point set obtained is a cross point position point set of underground flat steel; one-dimensional local maximum value selection is performed on each row and each column of the two-dimensional matrix, and a one-dimensional local maximum value point set obtained is a position point set of underground flat steel; the cross point set of underground flat steel and the position point set of underground flat steel are integrated, and a grounding grid topology structure is obtained. The application solves the problems of slow identification process and high misjudgment when a person obtains a grounding grid topology structure through magnetic response data of the grounding grid, improves the identification efficiency and accuracy, and has the advantages of simple algorithm and small calculation amount. BRIEF DESCRIPTION OF DRAWINGS
[0032] The specific effects of the application will be further described below in combination with the drawings and examples, and the drawings are as follows:
[0033] Figure 1 is a magnetic field distribution model of a current-carrying single conductor in the embodiment of the application;
[0034] Figure 2 is a distribution of |B x +B y | on the ground surface of a single current-carrying conductor in the embodiment of the application;
[0035] Figure 3 is a schematic diagram of orthogonal arrangement of a current-carrying conductor in the embodiment of the application;
[0036] Figure 4 is a distribution of |B x +B y | on the ground surface of two orthogonal current-carrying conductors in the embodiment of the application;
[0037] Figure 5 is a schematic diagram of movement of a structure element in magnetic response grid data and judgment of a local maximum value in the embodiment of the application;
[0038] Figure 6 is a schematic diagram of movement of a one-dimensional structure element in one-dimensional magnetic response grid data and judgment of a local maximum value in the embodiment of the application;
[0039] Figure 7 is a schematic diagram of display of two kinds of key feature points in the embodiment of the application;
[0040] Figure 8 is a flowchart of a grounding grid topology identification method in the embodiment of the application;
[0041] Figure 9 is a four-neighborhood / eight-neighborhood diagram of a two-dimensional matrix in an embodiment of the present application;
[0042] Figure 10 is a 5x5 grounding grid model in an embodiment of the present application
[0043] Figure 11 is 5x5 grounding grid simulation magnetic induction data in an embodiment of the present application;
[0044] Figure 12 is a bicubic interpolation diagram in an embodiment of the present application;
[0045] Figure 13 is a data preprocessing result in an embodiment of the present application;
[0046] Figure 14 is a topology structure identification result in an embodiment of the present application;
[0047] Figure 15 is a comparison between an identification result and an actual grounding grid conductor in an embodiment of the present application;
[0048] Figure 16 is a grounding grid topology identification device diagram in an embodiment of the present application. DETAILED DESCRIPTION
[0049] In order to have a clearer understanding of the technical features, objectives and effects of the present application, the specific embodiments of the present application will now be described in detail with reference to the accompanying drawings.
[0050] In the present embodiment, first, the relevant principles of grounding grid topology structure based on key feature point detection of magnetic response data are briefly introduced and analyzed, and it should be noted that the following three principles do not belong to the prior art and are key implementation principles of the technical solution of the present application:
[0051] (1) Key feature point detection principle
[0052] For example, the distribution model of the magnetic field of a current-carrying single conductor is as follows Figure 1 As shown in the figure, the conductor is placed at a depth h, the soil is a homogeneous medium with magnetic permeability μ, an xyz rectangular coordinate system is established with point O on the conductor as the coordinate origin, the conductor passes through the x-axis, the current inside the conductor is I, the y-axis is perpendicular to the conductor, and the xOy plane is parallel to the ground, P is a detection point on the ground, the vertical distance from the conductor is ρ, and y represents the distance from the projection point of the P point on the xOy plane to the conductor.
[0053] According to the Biot-Savart law, the magnetic induction intensity module generated by the conductor at point P is:
[0054]
[0055] Due to ρ 2 =h 2 +y 2 The component of the magnetic field in the y direction is:
[0056]
[0057] Meanwhile, the magnetic field also produces a component in the x-direction:
[0058] |B x |=0
[0059] Therefore, the magnetic induction intensity of the magnetic field in the horizontal direction is:
[0060]
[0061] Simulation software can be used to draw a single current-carrying conductor on the Earth's surface |B x +B y The distribution of | is as follows Figure 2 As shown.
[0062] According to the above formula and Figure 2 It can be seen that in the case of a single current-carrying conductor, the magnetic field |B| in the horizontal direction at the Earth's surface x +B y The peak value exists only directly above the conductor perpendicular to the water surface. Therefore, the magnetic response data is maximum when the detection coil is above the conductor, i.e., when y=0. The magnetic response data will attenuate when the coil is far away from the flat steel. Based on this, the peak value can be determined to be the location of the grounding grid conductor.
[0063] Meanwhile, when local download flat steel is arranged in a cross pattern, such as Figure 3 As shown.
[0064] The magnetic fields generated by two current-carrying flat steel bars in the horizontal direction will superimpose. As shown in the previous model of a single current-carrying conductor, the magnetic induction intensity in the horizontal direction peaks directly above the flat steel bars. Therefore, after the magnetic fields of the two intersecting flat steel bars are superimposed, the magnetic induction intensity will peak directly above the intersection point. The magnetic field in the horizontal direction of the Earth's surface when the flat steel bars are intersecting is shown in Figure B. x +B y |Distribution as follows Figure 4 As shown.
[0065] Based on the above two magnetic field data characteristics, this embodiment proposes a method to use two-dimensional local maxima points of magnetic response gridded data as key feature points at the intersection of flat steel bars, and one-dimensional local maxima points as key feature points of the underground flat steel bar location. The method is to fuse the key feature points at the intersection of flat steel bars and the key feature points of the flat steel bar location to form a grounding grid topology image.
[0066] (2) Two-dimensional local maximum point as the key feature point principle of flat steel intersection
[0067] According to Figure 4 It can be seen that at the intersection of underground conductors, the magnetic response data above the intersection is significantly greater than that in the surrounding area. Therefore, after obtaining the grid data of the magnetic response, a two-dimensional structure element of a certain size is constructed, as shown in Figure 5 A 3x3 square structure element is constructed.
[0068] The structure element can move in the grid magnetic response data. The movement of the two-dimensional structure element is similar to the movement of the convolution kernel in the convolution neural network. While moving, it is determined whether the data at the center of the structure element is greater than the data around it. If it is greater, it meets the magnetic field distribution of the orthogonal current-carrying conductor on the ground surface, and can be saved as the key feature point data of the flat steel intersection, as shown in Figure 5 The data at position 10 obviously meets the local maximum value rule and can be saved as the key feature point data of the flat steel intersection.
[0069] (3) One-dimensional local maximum point as the key feature point principle of underground flat steel position
[0070] According to Figure 2 It can be seen that the magnetic response data above the conductor is greater than that away from the conductor. Therefore, a one-dimensional data is selected in the two-dimensional grid magnetic response data, and a one-dimensional structure element is constructed, as shown in Figure 6 A structure element with a capacity of 3 is constructed.
[0071] The structure element can move in the one-dimensional magnetic response data, and it is determined whether the data at the center of the one-dimensional structure element is greater than the data on both sides. If it is greater, it meets the magnetic field distribution of the single current-carrying conductor on the ground surface, and can be saved as the key feature point data of the flat steel position. As shown in Figure 6 The position of data 7 in the right one-dimensional data meets the one-dimensional local maximum condition and is saved as the key feature point data of the flat steel position.
[0072] After one-dimensional local maximum value judgment is performed on all columns and rows of the two-dimensional grid magnetic response data, the intersection flat steel position key feature points and the flat steel position key feature points are displayed in gray, and the obtained result is as shown in Figure 7 Thus, it can be analyzed that the underground flat steel is arranged in a cross shape.
[0073] In the actual analysis of the grounding grid topology structure by using the magnetic response data, since the detection equipment is pushed by manpower, the collection equipment cannot guarantee uniform speed driving, and meanwhile, due to the influence of the ground transformer substation equipment, the detection instrument needs to stop or detour when driving to a certain position, therefore, the collected data are discrete and non-uniform, and in the key feature point detection of the original magnetic response data of the grounding grid, the original magnetic response data needs to be preprocessed so as to facilitate the subsequent extraction of the grounding grid structure. The method of image processing is adopted to process the magnetic response data of the grounding grid, and the key feature points are extracted by using the processed magnetic response data to obtain the grid structure of the grounding grid. The specific process is as shown in Figure 8 The specific process is as shown in
[0074] S1: acquiring original magnetic response data of the grounding grid;
[0075] S2: preprocessing the original magnetic response data to obtain preprocessed magnetic response data;
[0076] S3: detecting key feature points based on the preprocessed magnetic response data, and the specific steps include:
[0077] The local maximum value method is adopted to select the two-dimensional local maximum value of the two-dimensional matrix formed by the preprocessed magnetic response data, and the obtained two-dimensional local maximum value point set is the position point set of the underground flat steel intersection point;
[0078] The one-dimensional local maximum value of each row of the two-dimensional matrix is selected, and the one-dimensional local maximum value of each column is selected, and the obtained one-dimensional local maximum value point set is the position point set of the underground flat steel;
[0079] S4: integrating the underground flat steel intersection point set and the underground flat steel position point set to obtain the data matrix of the position information of the grounding grid topology structure.
[0080] It should be noted that the magnetic response data refers to the alternating signal generated by the sensing coil in the horizontal direction due to the influence of the current-carrying flat steel.
[0081] Specifically, the magnetic response data preprocessing in S2 includes data normalization and data interpolation. Since the magnetic response data is affected by the grid structure and the current strength, the range of the magnetic response data is indefinite, and in order to facilitate subsequent data processing, the data must be in the same scale, that is, normalization processing is needed. In this embodiment, the maximum value normalization is adopted, that is, the maximum value of the data is regarded as 1, the minimum value of the data is regarded as 0, and the rest of the data is proportionally corresponding to the value between 0 and 1.
[0082] For discrete magnetic response data, the present embodiment adopts a bicubic interpolation algorithm. The bicubic interpolation is to select the values of the nearest 16 points around the point to be interpolated and then to obtain the value of the point to be interpolated by weighted average. The weight of each point is determined by the distance from the point to the point to be interpolated. The distance includes the horizontal and vertical distances. Thus, the value of the point to be interpolated is obtained according to the values of the 16 points and the weight influence of the points.
[0083] In the identification of key feature points of the magnetic response data, the local maximum method is adopted in the present embodiment. The local maximum method of the two-dimensional matrix is divided into four-neighborhood and eight-neighborhood local maximum. The four-neighborhood maximum means that the value is greater than or equal to the value of each point on the four-connected region. The eight-neighborhood maximum means that the value is greater than or equal to the value of each point on the eight-connected region.
[0084] As shown in Figure 9 the magnetic response data after preprocessing is a two-dimensional numerical matrix. (i-1, j-1), (i-1, j), (i-1, j+1), (i, j-1), (i, j), (i, j+1), (i+1, j-1), (i+1, j), and (i+1, j+1) are coordinate points in the matrix. Let the corresponding numerical values be Z(i-1, j-1), Z(i-1, j), Z(i-1, j+1), Z(i, j-1), Z(i, j), Z(i, j+1), Z(i+1, j-1), Z(i+1, j), and Z(i+1, j+1).
[0085] If Z(i, j) is a four-neighborhood two-dimensional local maximum point, it is shown in the following formula.
[0086] Z(i, j) ≥ max(Z(i, j-1), Z(i, j+1), Z(i-1, j), Z(i+1, j))
[0087] If Z(i, j) is an eight-neighborhood two-dimensional local maximum point, it is shown in the following formula.
[0088]
[0089] The positions in the two-dimensional matrix that meet the four-neighborhood or eight-neighborhood local maximum condition are assigned a value of 1, and the remaining positions are assigned a value of 0. In this way, a two-dimensional local maximum point set, i.e., a set of position points of the underground flat steel intersection, is obtained.
[0090] After the selection of the two-dimensional local maximum points is completed, the one-dimensional local maximum of each row of the two-dimensional matrix is selected to determine the position points of the underground flat steel. The positions that meet the one-dimensional local maximum condition are assigned a value of 1, and the remaining positions are assigned a value of 0. Then, the one-dimensional local maximum of each column is selected. Similarly, the positions that meet the one-dimensional local maximum condition are assigned a value of 1, and the remaining positions are assigned a value of 0.
[0091] Finally, the underground flat steel intersection dataset matrix and the underground flat steel position dataset matrix are integrated to form a data matrix reflecting the complete grounding grid topology position information, wherein the conductor part is 1 and the non-conductor part is 0.
[0092] In order to verify the implementation effect of the present application, a specific grounding grid model is selected for simulation experiment in this embodiment.
[0093] A 5*5 grounding grid model is built through COMSOL platform. As shown in Figure 10 , the conductor burial depth is determined to be 1m, the instrument detection height is 0.2m, the current injection point is at (3, 18), the current extraction point is at (18, 3), the injection current size is 5A, and the conductor radius is 8mm. The simulation result is shown in Figure 11 , the magnetic induction intensity data is derived, and the magnetic response data processing flow is simulated using the magnetic induction intensity data.
[0094] The original magnetic response data is normalized, and the processing formula is as follows
[0095]
[0096] Wherein, z represents the original magnetic response dataset, z' represents the dataset after maximum and minimum normalization processing, min(z) and max(z) represent the maximum and minimum values in the original magnetic response dataset z.
[0097] After the original magnetic response data is normalized, data interpolation is performed to obtain the gridded data. In this embodiment, a bicubic interpolation algorithm is used. The bicubic interpolation is to select the nearest 16 values around the to-be-solved value for weighted average, and the weight of each point is determined by the distance from the point to the to-be-solved point. This distance includes the horizontal and vertical distances. Thus, the value at the interpolation point is obtained according to the values of the 16 points and the weight influence of these points, as shown in Figure 12 .
[0098] Figure 12 P point in the middle is the interpolation point, and u and v are the distances of P point to Q point in x and y directions. There are various algorithms for the weighting coefficient, and the commonly used BiCubic is used as the bicubic interpolation base function, and the function is:
[0099]
[0100] a can take any value, then the weight value of Q point relative to P point is W G23 =W(v)*W(u), and the weight values of other 15 pixel points are calculated and added to obtain the to-be-interpolated data W G of P point.
[0101]
[0102] After the original magnetic response data is preprocessed, the effect of the preprocessing is shown in Figure 13 . The topological structure of the preprocessed magnetic response data is identified by using the key feature point extraction method of two-dimensional local maximum and one-dimensional local maximum. The identification result is shown in Figure 14 . The actual conductor part of the 5*5 grounding grid is shown in Figure 15 . According to the comparison of Figure 14 and Figure 15 , it can be seen that the key feature point detection method of the grounding grid magnetic response can accurately identify the topological structure of the grounding grid.
[0103] In other embodiments of the present application, as shown in Figure 16 , a grounding grid topological identification device based on key feature point detection of magnetic response data is also provided, comprising the following modules:
[0104] The data acquisition module 1 is used to acquire original magnetic response data of the grounding grid.
[0105] The preprocessing module 2 is used to preprocess the original magnetic response data to obtain preprocessed magnetic response data.
[0106] The key feature point detection module 3 is used to detect key feature points based on the preprocessed magnetic response data, and is specifically used for:
[0107] The local maximum method is used to select two-dimensional local maximum of the two-dimensional matrix formed by the magnetic response data, and the obtained two-dimensional local maximum point set is the underground flat steel intersection point position point set;
[0108] The one-dimensional local maximum of each row of the two-dimensional matrix is selected, and the one-dimensional local maximum of each column is selected, and the obtained one-dimensional local maximum point set is the underground flat steel position point set;
[0109] The topological structure identification module 4 is used to integrate the underground flat steel intersection point set and the underground flat steel position point set to obtain a data matrix of the topological structure position information of the grounding grid.
[0110] In other embodiments of the present application, an electronic device is also provided, which comprises a memory and a processor, and the memory stores a computer program, which is executed by the processor to perform the steps of the grounding grid topological identification method.
[0111] In other embodiments of the present application, a non-transitory computer readable storage medium is also provided, which stores a computer program, and the computer program is executed by a processor to implement the steps of the grounding grid topological identification method.
[0112] It should be noted that, in the present document, the terms "comprising", "comprising" or any other variant thereof are intended to cover non-exclusive inclusions, so that a process, method, article or system that includes a list of elements not only includes those elements, but also includes other elements not explicitly listed, or inherent to such a process, method, article or system. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of other identical elements in the process, method, article or system that includes the element.
[0113] The above-mentioned embodiment numbers of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments. In the unit claims of several devices, several of these devices can be embodied by the same hardware item. The use of the words first, second, and third does not represent any order, and these words can be interpreted as identification.
[0114] The above is only the preferred embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent process transformation using the content of the present application specification and drawings, or directly or indirectly applied to other related technical fields, are also included in the patent protection scope of the present application.
Claims
1. A ground net topology identification method based on key feature point detection of magnetic response data, characterized in that, The method comprises the following steps: obtaining original magnetic response data of the grounding grid; preprocessing the original magnetic response data to obtain preprocessed magnetic response data; based on the preprocessed magnetic response data, detecting key feature points, specifically comprising: using a local maximum value method to select two-dimensional local maximum values of a two-dimensional matrix formed by the preprocessed magnetic response data, and a two-dimensional local maximum value point set obtained by the selection is a cross point position point set of the underground flat steel; selecting one-dimensional local maximum values of each row of the two-dimensional matrix, and selecting one-dimensional local maximum values of each column, and a one-dimensional local maximum value point set obtained by the selection is a position point set of the underground flat steel; integrating the cross point set of the underground flat steel and the position point set of the underground flat steel to obtain a data matrix of the position information of the grounding grid topology structure.
2. The method of claim 1, wherein, The preprocessing of the original magnetic response data comprises data normalization and data interpolation processing.
3. The method of claim 2, wherein, The data normalization adopts maximum value normalization, taking the maximum value of the data as 1 and the minimum value of the data as 0, and proportionally corresponding all other data to values between 0 and 1.
4. The method of claim 2, wherein, The data interpolation processing adopts a bicubic interpolation algorithm, selects the nearest 16 points around a point to be interpolated, performs weighted average on the 16 points according to the weights of the points, and takes the result of the weighted average as the value of the point to be interpolated, wherein the weight of each point is determined by the horizontal distance and the vertical distance of the point to the point to be interpolated.
5. The method of claim 1, wherein, The two-dimensional local maximum value selection of the two-dimensional matrix formed by the preprocessed magnetic response data using the local maximum value method comprises: selecting four-neighborhood maximum values or eight-neighborhood local maximum values of the two-dimensional matrix; the four-neighborhood maximum value means that the value is greater than or equal to the value of each point in a four-connected region, and the eight-neighborhood local maximum value means that the value is greater than or equal to the value of each point in an eight-connected region.
6. The grounding grid topology identification method according to claim 1, assigning a value of 1 to a position in the two-dimensional matrix that meets the two-dimensional local maximum value condition, and assigning a value of 0 to the rest.
7. The method of claim 1, wherein, assigning a value of 1 to a position in each row and each column of the two-dimensional matrix that meets the one-dimensional local maximum value condition, and assigning a value of 0 to the rest.
8. A ground net topology identification device based on key feature point detection of magnetic response data, characterized in that, The method comprises the following modules: a data acquisition module for acquiring original magnetic response data of the grounding grid; a preprocessing module for preprocessing the original magnetic response data to obtain preprocessed magnetic response data; a key feature point detection module for detecting key feature points based on the preprocessed magnetic response data, specifically for: using a local maximum value method to select two-dimensional local maximum values of a two-dimensional matrix formed by the preprocessed magnetic response data, and a two-dimensional local maximum value point set obtained by the selection is a cross point position point set of the underground flat steel; selecting one-dimensional local maximum values of each row of the two-dimensional matrix, and selecting one-dimensional local maximum values of each column, and a one-dimensional local maximum value point set obtained by the selection is a position point set of the underground flat steel; a topology structure identification module for integrating the cross point set of the underground flat steel and the position point set of the underground flat steel to obtain a data matrix of the position information of the grounding grid topology structure.
9. An electronic device, comprising: The electronic device comprises a memory and a processor, and the memory stores a computer program, which, when executed by the processor, performs the steps of the grounding grid topology identification method according to any one of claims 1-7. 10.A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, implements the steps of the grounding grid topology identification method according to any one of claims 1-7.