Ground line intersection point positioning method, apparatus, and media

Abstract

The application provides a grounding wire and tower intersection positioning method, device and medium. The method comprises: acquiring a grounding wire point cloud and a tower point cloud; determining a first candidate intersection region by using an average Euclidean distance and a point density distribution between the grounding wire point cloud obtained by a K nearest neighbor algorithm and a preset number of tower point clouds; performing a screening operation on the first candidate intersection region to obtain a plurality of second candidate intersection regions; performing a merging processing on the plurality of second candidate intersection regions to obtain a target intersection region; projecting the point cloud in the target intersection region onto a local principal direction vector of the intersection region to obtain an accurate position of the grounding wire and tower intersection; through twice intersection region screening and merging processing on the second candidate intersection region, the accuracy of the intersection region positioning of the grounding wire point cloud and the preset number of tower point clouds is improved, and through the projection operation on the point cloud in the target intersection region, the accurate intersection position of the grounding wire and the tower is obtained.

Description

Technical Field

[0001] This application belongs to the field of power facility inspection technology, and relates to a method, equipment and medium for locating the intersection of grounding wire and tower. Background Technology

[0002] In the field of intelligent inspection technology for power facilities, accurate spatial positioning based on grounding wire feature points and tower point cloud data is a core technical link to ensure the safe and stable operation of transmission lines. However, achieving this task faces a series of severe technical challenges, mainly including: Grounding wires, due to their typically small physical diameter, can only generate sparse and discrete point sets in point cloud data acquired by sensors such as LiDAR. Compared to the massive tower structure, this point set has a significantly lower signal-to-noise ratio, making it difficult to detect and identify reliably and stably in complex point cloud backgrounds. Tower structures themselves are highly complex and diverse, and in actual operating environments, their surfaces may corrode due to long-term exposure, and the overall structure may deform due to external forces or material aging. More critically, the connection points between the grounding wire and the tower, such as the connection surface or welding area of ​​the grounding bolt, often lack sufficiently significant geometric or textural features in the point cloud data that maintain consistency across different samples. This uncertainty makes developing algorithms that can adapt to various operating conditions and stably identify these connection points extremely difficult. Therefore, improving the accuracy of the intersection point location between the grounding wire point cloud and the tower point cloud data has become an urgent technical problem to be solved. Summary of the Invention

[0003] This application provides a method, device, and medium for locating the intersection of a grounding wire and a tower, which improves the accuracy of intersection location.

[0004] In a first aspect, this application provides a method for locating the intersection of a grounding wire and a tower. The method includes: acquiring a grounding wire point cloud and a tower point cloud; determining the average Euclidean distance and point density distribution between the grounding wire point cloud and a preset number of tower point clouds; determining a first candidate intersection region based on the average Euclidean distance and the point density distribution; performing a filtering operation on the first candidate intersection region to obtain a plurality of second candidate intersection regions; merging the plurality of second candidate intersection regions to obtain a target intersection region; and performing a projection operation on the point cloud within the target intersection region to obtain the intersection position of the grounding wire and the tower.

[0005] In the grounding wire and tower intersection location method provided in this application embodiment, by screening the intersection area twice and merging the second candidate intersection area, the fine positioning of the intersection area corresponding to the grounding wire point cloud and the preset number of tower point clouds is achieved, which improves the accuracy of the positioning of the intersection area corresponding to the grounding wire point cloud and the preset number of tower point clouds. By projecting the point cloud in the target intersection area, the accurate intersection position of the grounding wire and the tower is obtained.

[0006] In one implementation of the first aspect, the step of filtering the first candidate intersection region to obtain a plurality of second candidate intersection regions includes: acquiring a plurality of grounding wire sampling points corresponding to the grounding wire point cloud; sequentially searching the tower point cloud near each grounding wire sampling point to find its corresponding nearest neighbor tower point; sequentially determining the spatial proximity and local geometric position of each grounding wire sampling point and the nearest tower point; and based on the plurality of spatial proximity and the local geometric position corresponding to the plurality of spatial proximity, performing a filtering operation on the first candidate intersection region to obtain a plurality of second candidate intersection regions.

[0007] In one implementation of the first aspect, the step of merging multiple second candidate intersection regions to obtain a target intersection region includes: determining the centroid of each second candidate intersection region; extracting the principal direction vector of each second candidate intersection region sequentially based on principal component analysis; determining the Euclidean distance between any two centroids sequentially; determining directional similarity based on the principal direction vectors of the second candidate intersection regions where the two centroids are located; and merging the two second candidate intersection regions where the two centroids are located if the Euclidean distance between the two centroids is less than a preset distance threshold and the directional similarity is less than a preset angle threshold, to obtain the target intersection region.

[0008] In one implementation of the first aspect, the expression corresponding to determining directional similarity is:

[0009]

[0010] in, and S represents the local principal direction vector of the two second candidate intersection regions, respectively. dir Indicates directional similarity.

[0011] In one implementation of the first aspect, the step of projecting the point cloud within the target intersection region to obtain the intersection position of the grounding wire and the tower includes: extracting the local principal direction vector of the target intersection region based on principal component analysis; and sequentially projecting the point cloud within the target intersection region onto the local principal direction vector of the target intersection region to obtain the precise position of the intersection of the grounding wire and the tower.

[0012] In one implementation of the first aspect, the expression corresponding to the step of sequentially projecting the point cloud within the target intersection region onto the local principal direction vector of the target intersection region is:

[0013]

[0014] in, This indicates the location of the intersection between the grounding wire and the tower, where N represents the number of point clouds within the target intersection area. This represents the i-th point cloud within the target intersection region. The unit vector representing the principal direction of the target intersection region.

[0015] Secondly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the grounding wire and tower intersection positioning method described in any one of the first aspects of this application.

[0016] Thirdly, embodiments of this application provide an electronic device, the electronic device comprising: a memory storing a computer program; and a processor communicatively connected to the memory, which, when the computer program is invoked, executes the grounding wire and tower intersection positioning method described in any of the first aspects of embodiments of this application.

[0017] As described above, the grounding wire and tower intersection positioning method, equipment, and medium described in this application have the following beneficial effects:

[0018] 1) By filtering the intersection areas twice and merging the second candidate intersection areas, the fine positioning of the intersection areas corresponding to the grounding wire point cloud and the preset number of tower point clouds is achieved, which improves the accuracy of the positioning of the intersection areas corresponding to the grounding wire point cloud and the preset number of tower point clouds. By projecting the point cloud in the target intersection area, the accurate intersection position of the grounding wire and the tower is obtained, which helps maintenance personnel to quickly and accurately find the grounding connection point, facilitates inspection, tightening, anti-corrosion treatment or replacement of damaged parts, and improves the work efficiency of maintenance personnel.

[0019] 2) By determining the spatial proximity and local geometric position of the grounding wire sampling points corresponding to the grounding wire point cloud and the tower body point closest to each grounding wire sampling point, the first candidate intersection area is filtered based on the spatial proximity and local geometric position to obtain multiple second candidate intersection areas. This achieves a second filtering of the first candidate intersection area, resulting in more accurate multiple second candidate intersection areas, which provides accurate candidate intersection areas for subsequent determination of the intersection position of the grounding wire and the tower.

[0020] 3) The second intersection regions are merged based on the Euclidean distance and orientation similarity between any two second candidate intersection regions to obtain the target intersection region. This realizes another filtering operation on the second candidate intersection regions, narrows down the position of the intersection region, and improves the positional accuracy of the target intersection region. Attached Figure Description

[0021] Figure 1A The diagram shows a hardware application scenario corresponding to the grounding wire and tower intersection positioning method provided in one embodiment of this application.

[0022] Figure 1B The flowchart shown is a method for locating the intersection of a grounding wire and a tower according to an embodiment of this application.

[0023] Figure 2 The flowchart shown is a process for determining a second candidate intersection region according to an embodiment of this application.

[0024] Figure 3 The flowchart shown is a process for determining the target intersection region according to an embodiment of this application.

[0025] Figure 4 The flowchart shown is a process for determining the location of an intersection point according to an embodiment of this application.

[0026] Figure 5 The diagram shown is a structural diagram of an electronic device provided in an embodiment of this application.

[0027] Component designation explanation

[0028] Steps S11-S16, Step 51: Processor

[0029] Steps S21-S24, 52. Non-volatile storage medium

[0030] Steps 53 (S31-S35) System Bus

[0031] Steps S41-S42, 54. Internal Memory

[0032] 50 Electronic devices 55 Network interfaces Detailed Implementation

[0033] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0034] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. Therefore, the drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0035] The following embodiments of this application provide a method, device, and medium for locating the intersection of a grounding wire and a tower, including but not limited to the hardware application scenarios listed in this embodiment. The following description will take the hardware application scenario corresponding to the grounding wire and tower intersection location method as an example.

[0036] like Figure 1A As shown in the illustration, this application provides a hardware application scenario diagram corresponding to a grounding wire and tower intersection location method, specifically including: a transmission tower, a drone, and electronic equipment. The drone and electronic equipment are wirelessly connected. The drone collects tower point clouds and grounding wire point clouds from the transmission tower and wirelessly transmits them to the electronic equipment. The electronic equipment acquires the grounding wire point cloud and tower point cloud transmitted by the drone, performs two filtering operations on the intersection areas corresponding to the grounding wire point cloud and a preset number of tower point clouds to determine the target intersection area, and projects the point cloud within the target intersection area to obtain the precise intersection position of the grounding wire and the tower.

[0037] The technical solutions in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0038] like Figure 1B As shown in the figure, this embodiment provides a flowchart of a method for locating the intersection of a grounding wire and a tower, as follows: Figure 1B As shown, the grounding wire and tower intersection positioning method provided in this application embodiment includes the following steps S11 to S16.

[0039] S11, acquire the point cloud of the grounding wire and the point cloud of the tower.

[0040] For example, the grounding wire point cloud can be obtained based on the grounding wire point cloud extraction method.

[0041] It should be noted that the methods for obtaining grounding wire point clouds and tower point clouds listed above are merely illustrative examples. In practical applications, other suitable methods can be selected to obtain grounding wire point clouds and tower point clouds according to specific application requirements. This application does not impose any restrictions on this.

[0042] S12, determine the average Euclidean distance and point density distribution between the grounding wire point cloud and the preset number of tower point clouds.

[0043] The preset number of pole point clouds can be represented by K. In practical applications, any other suitable number of pole point clouds can be selected according to specific application requirements. This application does not impose any restrictions on this.

[0044] For example, the K-Nearest Neighbor (KNN) algorithm can be used to calculate the average Euclidean distance and point density distribution between the grounding wire point cloud and a preset number of tower point clouds.

[0045] For example, for each grounding wire point cloud p, k tower points p are calculated based on KNN. i The average Euclidean distance D knn (p), and simultaneously calculate the point density distribution within this local region.

[0046] The expression for the average Euclidean distance is:

[0047]

[0048] S13, Based on the average Euclidean distance and the point density distribution, determine the first candidate intersection region.

[0049] Specifically, by comprehensively judging the spatial proximity between the grounding wire point and the tower point (i.e., D) knn The p-value, as well as the density of the tower point cloud in the local area, can effectively focus on the area where the point cloud is dense and the two types of structures are closely connected, so as to initially identify the possible intersection location, that is, the first candidate intersection area.

[0050] For example, iterate through each point p in the grounding wire point cloud. For each point p, use the K-nearest neighbor algorithm to find the k nearest points to it in the tower point cloud. Calculate the average Euclidean distance from point p to these k nearest tower points, denoted as D. knn (p). D knn (p) is a quantitative indicator of "spatial proximity", D knnThe smaller the value of (p), the closer the point on the grounding wire is to the tower structure. Within a small local area centered on point p, calculate the number of tower points falling into this area, and use this as the "point density" index of the area. The higher the density, it indicates that the tower structure at this position is more solid and reliable, rather than sparse noise points.

[0051] Specifically, two preset thresholds are set: a distance threshold T_d and a density threshold T_p. For each grounding wire point p, the following judgment is made: if and only if D knn (p)<T_d (the distance is sufficiently close) and the local tower point density>T_p (the density is sufficiently high), the point p is determined to satisfy the distance and density conditions. All grounding wire points p that satisfy the above distance threshold and density threshold, together with their respective adjacent tower body point cloud regions, are combined and clustered to form one or more "first candidate intersection regions".

[0052] S14, performing a screening operation on the first candidate intersection regions to obtain a plurality of second candidate intersection regions.

[0053] S15, performing merging processing on the plurality of second candidate intersection regions to obtain a target intersection region.

[0054] S16, performing a projection operation on the point cloud in the target intersection region to obtain the intersection position of the grounding wire and the tower.

[0055] An embodiment of the present application provides a method for locating the intersection of a grounding wire and a tower. By performing two screenings on the intersection regions corresponding to the grounding wire point cloud and a preset number of tower point clouds and merging the screened second candidate intersection regions, the target intersection region is obtained, which improves the accuracy of determining the target intersection region corresponding to the grounding wire point cloud and the preset number of tower point clouds. By performing the projection operation on the point cloud in the target intersection region, the accurate intersection position of the grounding wire and the tower is obtained, which greatly improves the accuracy of intersection positioning.

[0056] As Figure 2 shown, an embodiment of the present application provides a flowchart for determining a second candidate intersection region. As Figure 2 shown, the method for determining a second candidate intersection region provided by the embodiment of the present application includes the following steps S21 to S24.

[0057] S21, acquiring a plurality of grounding wire sampling points corresponding to the grounding wire point cloud.

[0058] Exemplarily, a plurality of grounding wire sampling points corresponding to the grounding wire point cloud can be acquired based on a uniform sampling or non-uniform sampling method.

[0059] It should be noted that the two methods listed above for obtaining multiple grounding sampling points corresponding to the grounding point cloud are merely illustrative examples. In actual applications, any method can be selected to obtain grounding sampling points according to the specific application scenario, and this application does not impose any restrictions on this.

[0060] S22, sequentially search the tower point cloud near each grounding wire sampling point to find its corresponding nearest neighbor tower point.

[0061] Specifically, the tower point closest to the grounding wire sampling point is determined.

[0062] S23, sequentially determine the spatial proximity and local geometric position of each grounding wire sampling point and the nearest tower body point.

[0063] Spatial proximity refers to the Euclidean distance between a sampling point on the grounding wire and the nearest point on the tower in three-dimensional space. This distance is calculated to quantify the degree of "proximity." A smaller distance represents higher spatial proximity, indicating that the grounding wire sampling point is physically very close to the tower.

[0064] Local geometric location refers to the local principal direction of the point cloud within the local neighborhood of the grounding wire sampling point and its nearby tower points. The local principal direction is an eigenvector calculated by principal component analysis of the point cloud within this local region (for both the grounding wire point and the tower point). It describes the orientation and attitude of the grounding wire and tower structure near this point and is crucial geometric information for determining whether multiple candidate points belong to the same continuous intersection region.

[0065] For example, based on multiple spatial proximity and the local geometric positions corresponding to multiple spatial proximity, a filtering operation is performed on the first candidate intersection region to obtain multiple second candidate intersection regions, including: 1) Uniform sampling and pairing: Uniformly spaced sampling is performed on the grounding wire segments contained in the "first candidate intersection region" to obtain multiple "grounding wire sampling points". For each grounding wire sampling point, its nearest neighbor tower point is searched and determined in the tower point cloud to form a "sampling point-tower point" pairing. 2) For each "sampling point-tower point" pairing, its "spatial proximity", i.e., the Euclidean distance between the two points, is calculated. Principal component analysis is performed on each grounding wire sampling point and its corresponding nearest neighbor tower point in their respective local neighborhoods to calculate their "local geometric position", i.e., the local principal direction feature vector. 3) Filtering: Spatial proximity-based filtering: Traverse the Euclidean distances of all "sampling point-tower point" pairs, retaining only those pairs that are physically close enough in Euclidean distance. The retained sampling point-tower point pairs constitute a preliminary refined candidate point set. Local geometric location-based filtering: Analyze the refined candidate point set retained in the previous step. By calculating the directional similarity between the local principal direction vectors of the points in the refined candidate point set, determine whether they belong to the same structurally coherent intersection point.

[0066] For example, within a real intersection region, the local principal directions of all grounding wire sampling points should be basically consistent. Similarly, the local principal directions of all corresponding tower points should also show consistency or a smooth transition. If the local principal directions of some candidate points are found to differ too much from those of other adjacent candidate points, these points are considered noise or incorrect connection points and are eliminated. 4) After the above two rounds of screening, the set of candidate points that are close in location and have consistent geometric directions constitutes the final second candidate intersection region.

[0067] S24, based on the multiple spatial proximity and the local geometric positions corresponding to the multiple spatial proximity, a filtering operation is performed on the first candidate intersection region to obtain multiple second candidate intersection regions.

[0068] This application provides a method for determining a second candidate intersection region. In this method, by determining multiple grounding wire sampling points corresponding to the grounding wire point cloud and the spatial proximity and local geometric position of the tower point closest to each grounding wire sampling point, the first candidate intersection region is filtered based on the spatial proximity and local geometric position to obtain multiple second candidate intersection regions. This achieves a further filtering of the first candidate intersection region, resulting in more accurate multiple second candidate intersection regions, providing accurate candidate intersection regions for subsequent determination of the intersection position of the grounding wire and the tower.

[0069] like Figure 3As shown, this embodiment provides a flowchart for determining the target intersection region, as follows: Figure 3 As shown, the method for determining the target intersection region provided in this application embodiment includes the following steps S31 to S35.

[0070] S31, determine the centroid of each second candidate intersection region.

[0071] S32, Based on principal component analysis, extract the local principal direction vector of each second candidate intersection region in sequence.

[0072] For example, if there are 5 candidate intersection regions, then the local principal direction vector of each candidate intersection region is extracted sequentially based on principal component analysis. That is, each candidate intersection region corresponds to a local principal direction vector.

[0073] It should be noted that the number of second candidate intersection points listed above is only for illustrative purposes. In actual applications, any other suitable number of second candidate intersection point regions can be obtained according to specific application requirements and the specific scenario of filtering the first candidate intersection point region. This application does not impose any restrictions on this.

[0074] S33, determine the Euclidean distance between the two centroids in turn based on any two centroids.

[0075] Specifically, the expression for determining the Euclidean distance between two centroids includes:

[0076]

[0077] in, D represents the centroid coordinates of the two second candidate intersection regions; centroid This represents the Euclidean distance between the two centers of mass.

[0078] For example, if the number of second candidate intersection regions is 5, namely {S1, S2, S3, S4, S5}, and the centroids corresponding to each second candidate intersection region are {t1, t2, t3, t4, t5}, then the Euclidean distances between any two centroids are D. centroid1-2 D centroid1-3 D centroid1-4 D centroid1-5 D centroid2-3 D centroid2-4 D centroid2-5 D centroid3-4 D centroid3-5 D centroid4-5 .

[0079] S34, determine the directional similarity based on the local principal direction vector of the second candidate intersection region where any two centroids are located.

[0080] For example, if the centroids corresponding to the two second candidate intersection point regions are {t1, t2}, and the local principal direction vectors corresponding to the two second candidate intersection point regions are respectively... and

[0081] In some embodiments, the expression corresponding to determining directional similarity is:

[0082]

[0083] in, and S represents the local principal direction vector of the two second candidate intersection regions, respectively. dir Indicates directional similarity.

[0084] S35, if the Euclidean distance between any two centroids is less than a preset distance threshold and the directional similarity is less than a preset angle threshold, then the two second candidate intersection regions where the two centroids are located are merged to obtain the target intersection region.

[0085] For example, if the Euclidean distance D centroid1-2 Less than the preset distance threshold, and D centroid1-2 The directional similarity S corresponding to the two second candidate intersection regions is dir1-2 If the angle is less than the preset threshold, then D will be... centroid1-2 The two corresponding second candidate intersection regions are merged; similarly, other second candidate intersection regions that meet the preset distance threshold constraint and preset angle threshold constraint are merged in the same way to obtain the target intersection region.

[0086] It should be noted that the specific values ​​of the preset distance threshold and preset angle threshold in the above examples can be reasonably determined based on the specific scenario, and this application will not elaborate on this further.

[0087] This application provides a method for determining a target candidate intersection region. In this method, the second candidate intersection regions are merged based on the Euclidean distance and directional similarity between any two second candidate intersection regions to obtain the target intersection region. This achieves another filtering operation on the second candidate intersection regions, narrows down the position of the intersection region to obtain the target intersection region, and improves the positional accuracy of the target intersection region.

[0088] like Figure 4 As shown in the figure, this application provides a flowchart for determining the location of the intersection point, as follows: Figure 4 As shown, the method for determining the location of an intersection point provided in this application includes the following steps S41 to S42.

[0089] S41, Based on principal component analysis, extract the local principal direction vector of the target intersection region.

[0090] Specifically, the point cloud of the target intersection region is determined, and the covariance matrix of the point cloud of the target intersection region is calculated. Based on the covariance matrix, the eigenvalues ​​and eigenvectors are obtained. The eigenvector corresponding to the largest eigenvalue of the point cloud of the target intersection region is determined as the local principal direction vector of the target intersection region.

[0091] S42, the point cloud within the target intersection area is sequentially projected onto the local principal direction vector of the target intersection area to obtain the precise location of the intersection of the grounding wire and the tower.

[0092] In some embodiments, the expression corresponding to projecting the point cloud within the target intersection region onto the local principal direction vector of the target intersection region is:

[0093]

[0094] in, This indicates the location of the intersection between the grounding wire and the tower, where N represents the number of point clouds within the target intersection area. This represents the i-th point cloud within the target intersection region. The unit vector representing the main direction of the target intersection region.

[0095] In a method for determining the location of an intersection point provided in this application embodiment, the intersection point is located by projection method. The point cloud in the target intersection point area is sequentially projected onto the local principal direction vector of the target intersection point area to obtain the intersection point location, which greatly improves the accuracy of intersection point location.

[0096] The scope of the grounding wire and tower intersection location method described in this application is not limited to the execution order of the steps listed in this embodiment. Any solution implemented by adding, subtracting, or replacing steps in the prior art based on the principles of this application is included within the protection scope of this application.

[0097] In the several embodiments provided in this application, it should be understood that the disclosed methods can be implemented in other ways. For example, they can also be implemented through device embodiments. For instance, the division of modules / units is merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, or indirect coupling or communication connection between devices, modules, or units, and can be electrical, mechanical, or other forms.

[0098] The modules / units described as separate components may or may not be physically separate. The components shown as modules / units may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules / units can be selected to achieve the objectives of the embodiments of this application, depending on actual needs. For example, the functional modules / units in the various embodiments of this application may be integrated into one processing module, or each module / unit may exist physically separately, or two or more modules / units may be integrated into one module / unit.

[0099] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0100] This application also provides an electronic device. Figure 5 The diagram shown is a structural schematic of an electronic device 50 in one embodiment of this application. The grounding wire and tower intersection positioning method provided in this embodiment can be applied to... Figure 5 The electronic devices shown are 50, but not limited to these. For example... Figure 5 As shown, the electronic device 50 includes a processor 51, a memory, a system bus 53, and a network interface 55. The memory may include a non-volatile storage medium 52 and internal memory 54. The non-volatile storage medium 52 may store an operating system and a computer program. The computer program includes program instructions, which, when executed, cause the processor to perform any of the grounding wire and tower intersection location methods provided in the embodiments of this application.

[0101] The processor provides computing and control capabilities, supporting the operation of the entire computer device.

[0102] The internal memory 54 provides an environment for the execution of a computer program in a non-volatile storage medium. When the computer program is executed by the processor, it enables the processor to execute any of the grounding wire and tower intersection location methods provided in the embodiments of this application.

[0103] This network interface 55 is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 5The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0104] It should be understood that processor 51 can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among these, the general-purpose processor can be a microprocessor or any conventional processor.

[0105] The electronic device 50 in this application embodiment may include terminal devices such as tablet computers, laptop computers, mobile phones, supercomputers, and smart wearable devices. It can also be applied to databases, servers, and service response systems based on terminal artificial intelligence. This application embodiment does not impose any restrictions on the specific type of electronic device.

[0106] For example, electronic devices can be stations (STAION, ST) in WLANs, cellular phones, cordless phones, Session Initiation Protocol (SIP) phones, Wireless Local Loop (WLL) stations, handheld devices with wireless communication capabilities, computing devices or other processing devices connected to a wireless modem, computers, laptops, handheld communication devices, handheld computing devices, and / or other devices for communicating over wireless systems, as well as next-generation communication systems, such as mobile terminals in 5G networks, mobile terminals in future evolved Public Land Mobile Networks (PLMNs), or mobile terminals in future evolved Non-terrestrial Networks (NTNs).

[0107] This application also provides a computer-readable storage medium. Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing a processor. The program can be stored in a computer-readable storage medium, which is a non-transitory medium, such as random access memory, read-only memory, flash memory, hard disk, solid-state drive, magnetic tape, floppy disk, optical disk, and any combination thereof. The storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., solid-state drive (SSD)).

[0108] This application embodiment may also provide a computer program product comprising one or more computer instructions. When the computer instructions are loaded and executed on a computing device, all or part of the processes or functions described in this application embodiment are generated. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0109] When the computer program product is executed by a computer, the computer performs the method described in the foregoing method embodiments. The computer program product can be a software installation package; when the foregoing method is required, the computer program product can be downloaded and executed on the computer.

[0110] The descriptions of the processes or structures corresponding to the above figures each have their own emphasis. For parts of a process or structure that are not described in detail, please refer to the relevant descriptions of other processes or structures.

[0111] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A method for locating the intersection of a grounding wire and a tower, characterized in that, The method includes: Obtain the point cloud of the grounding wire and the point cloud of the tower; Determine the average Euclidean distance and point density distribution between the grounding wire point cloud and the point cloud of a preset number of towers; Based on the average Euclidean distance and the point density distribution, the first candidate intersection region is determined; The first candidate intersection region is filtered to obtain multiple second candidate intersection regions; Multiple second candidate intersection regions are merged to obtain the target intersection region; Project the point cloud within the target intersection area to obtain the intersection position of the grounding wire and the tower.

2. The method for locating the intersection of the grounding wire and the tower according to claim 1, characterized in that, The filtering operation on the first candidate intersection region yields multiple second candidate intersection regions, including: Based on obtaining multiple grounding wire sampling points corresponding to the grounding wire point cloud; Search the tower point cloud near each grounding wire sampling point in turn to find its corresponding nearest neighbor tower point; The spatial proximity and local geometric position of each grounding wire sampling point and the nearest tower point are determined sequentially; Based on multiple spatial proximity and the local geometric positions corresponding to multiple spatial proximity, a filtering operation is performed on the first candidate intersection region to obtain multiple second candidate intersection regions.

3. The method for locating the intersection of the grounding wire and the tower according to claim 1, characterized in that, The step of merging multiple second candidate intersection regions to obtain the target intersection region includes: Determine the centroid of each second candidate intersection region; Based on principal component analysis, the principal direction vector of each second candidate intersection region is extracted sequentially. The Euclidean distance between the two centroids is determined sequentially based on any two centroids. Directional similarity is determined based on the principal direction vector of the second candidate intersection region where any two centroids are located; If the Euclidean distance between any two centroids is less than a preset distance threshold and the directional similarity is less than a preset angle threshold, then the two second candidate intersection regions where the two centroids are located are merged to obtain the target intersection region.

4. The method for locating the intersection of the grounding wire and the tower according to claim 3, characterized in that, The expression corresponding to the determination of directional similarity is: in, and S represents the local principal direction vector of the two second candidate intersection regions, respectively. dir Indicates directional similarity.

5. The method for locating the intersection of the grounding wire and the tower according to claim 1, characterized in that, The step of projecting the point cloud within the target intersection area to obtain the intersection position of the grounding wire and the tower includes: Based on principal component analysis, the local principal direction vector of the target intersection region is extracted; The point cloud within the target intersection area is sequentially projected onto the local principal direction vector of the target intersection area to obtain the precise location of the intersection point between the grounding wire and the tower.

6. The method for locating the intersection of the grounding wire and the tower according to claim 5, characterized in that, The expression corresponding to projecting the point cloud within the target intersection region sequentially onto the local principal direction vector of the target intersection region is: in, This indicates the location of the intersection between the grounding wire and the tower, where N represents the number of point clouds within the target intersection area. This represents the i-th point cloud within the target intersection region. The unit vector representing the main direction of the target intersection region.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for locating the intersection of the grounding wire and the tower as described in any one of claims 1 to 6.

8. An electronic device, characterized in that, The electronic device includes: A memory that stores a computer program; The processor, which is communicatively connected to the memory, executes the grounding wire and tower intersection location method according to any one of claims 1 to 6 when calling the computer program.

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