Method, device, storage medium and electronic device for predicting wiring material information

Abstract

This invention discloses a method, apparatus, storage medium, and electronic device for predicting cabling material usage information. The method includes: acquiring an initial cabling path in a power distribution expansion scenario, and multiple initial trajectory points along the initial cabling path; filtering the multiple initial trajectory points according to a filtering strategy to obtain at least one target trajectory point; determining multiple key trajectory points based on the at least one target trajectory point, wherein the importance of the key trajectory points is higher than that of the target trajectory points in the initial cabling path; generating a target cabling path based on the multiple key trajectory points, and determining a target cabling distance in the power distribution expansion scenario based on the target cabling path; and predicting cabling material usage in the power distribution expansion scenario based on the target cabling distance and the target cabling path to obtain cabling material usage information. This invention solves the technical problem of low prediction accuracy for cabling material usage information.

Description

Technical Field

[0001] This invention relates to the field of cabling materials technology, and more specifically, to a method, apparatus, storage medium, and electronic device for predicting cabling material information. Background Technology

[0002] When surveying for low-voltage distribution expansion projects on outdoor power grids, it is necessary to assess and observe the site in order to estimate the route and length of the line, and then estimate the materials required for the expansion.

[0003] Currently, the Global Positioning System (GPS) is used to conduct on-site surveys for low-voltage power distribution expansion projects, obtaining location trajectory points and related information such as wiring materials. However, when the GPS system is used to obtain location trajectory points, it is affected by noise, which causes the obtained location trajectory points to deviate. As a result, there is a technical problem of low prediction accuracy of wiring material information.

[0004] There is currently no effective solution to the technical problem of low prediction accuracy of the aforementioned cabling material information. Summary of the Invention

[0005] This invention provides a method, apparatus, storage medium, and electronic device for predicting cabling material usage information, thereby at least solving the technical problem of low prediction accuracy of cabling material usage information.

[0006] According to one aspect of the invention, a method for predicting wiring material information is provided. The method includes: acquiring an initial wiring path in a power distribution expansion scenario, and multiple initial trajectory points on the initial wiring path; filtering the multiple initial trajectory points according to a filtering strategy to obtain at least one target trajectory point, wherein the filtering strategy is used to characterize the rules for filtering noise points present in the multiple initial trajectory points; determining multiple key trajectory points based on the at least one target trajectory point, wherein the importance of the key trajectory points is higher than the importance of the target trajectory points in the initial wiring path; generating a target wiring path based on the multiple key trajectory points, and determining a target wiring distance in the power distribution expansion scenario based on the target wiring path; and predicting wiring material usage in the power distribution expansion scenario based on the target wiring distance and the target wiring path to obtain wiring material information.

[0007] Optionally, filtering multiple initial trajectory points according to a filtering strategy to obtain at least one target trajectory point includes: obtaining the access status of multiple initial trajectory points respectively; in response to the access status of a first trajectory point being unaccessed, obtaining a first distance between the first trajectory point and a second trajectory point, wherein the first trajectory point is any point among the multiple initial trajectory points, and the second trajectory point is any point among the multiple initial trajectory points other than the first trajectory point; in response to the first distance being less than a first distance threshold, determining a neighborhood set of the first trajectory point; in response to the number of elements in the neighborhood set being greater than or equal to the number of target elements, determining the first trajectory point as a target trajectory point, and updating the access status of the first trajectory point to an accessed state; and determining multiple target trajectory points based on the updated access status of the multiple initial trajectory points.

[0008] Optionally, based on at least one target trajectory point, multiple key trajectory points are determined, including: selecting a target number of trajectory points from the multiple target trajectory points; generating a target number of trajectory groups based on the target number of trajectory points; obtaining the centroid coordinates of the target number of trajectory groups and the centroid points corresponding to the centroid coordinates; connecting the target number of centroid points to the starting point to generate a target number of target straight lines, wherein the starting point is obtained by selecting from multiple initial trajectory points; and determining multiple key trajectory points based on the target number of target straight lines.

[0009] Optionally, based on the target numerical line, multiple key trajectory points are determined, including: obtaining the second distance between the trajectory points in the trajectory group and the target line respectively; summing the multiple second distances to obtain the target sum value; and determining multiple key trajectory points based on the multiple target sum values.

[0010] Optionally, a target wiring path is generated based on multiple key trajectory points, and a target wiring distance is determined based on the target wiring path in the power distribution expansion scenario, including: obtaining the timestamps of multiple key trajectory points respectively; sorting the multiple key trajectory points based on the multiple timestamps to obtain sorted multiple key trajectory points; and obtaining the target wiring distance and target wiring path based on the sorted multiple key trajectory points.

[0011] Optionally, based on the sorted multiple key trajectory points, the target wiring distance and target wiring path are obtained, including: connecting the sorted multiple key trajectory points to obtain the target wiring path; determining multiple third distances based on the target wiring path; and summing the multiple third distances to obtain the target wiring distance.

[0012] Optionally, based on the target wiring distance and target wiring path, the wiring materials required in the power distribution expansion scenario are predicted to obtain wiring material information, including: determining the pole and tower material information in the wiring material information based on the target wiring path; determining the insulator material information in the wiring material information based on the pole and tower material information; and determining the line material information in the wiring material information based on the target wiring distance.

[0013] According to one aspect of the present invention, a device for predicting wiring material information is provided. The device further includes: a first acquisition unit, configured to acquire an initial wiring path in a power distribution expansion scenario, and a plurality of initial trajectory points on the initial wiring path; a filtering unit, configured to filter the plurality of initial trajectory points according to a filtering strategy to obtain at least one target trajectory point, wherein the filtering strategy is used to characterize the rules for filtering noise points present in the plurality of initial trajectory points; a first determination unit, configured to determine a plurality of key trajectory points based on at least one target trajectory point, wherein the importance of the key trajectory points is higher than the importance of the target trajectory points in the initial wiring path; a second determination unit, configured to generate a target wiring path based on the plurality of key trajectory points, and determine a target wiring distance in the power distribution expansion scenario based on the target wiring path; and a second acquisition unit, configured to predict wiring material usage in the power distribution expansion scenario based on the target wiring distance and the target wiring path to obtain wiring material information.

[0014] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein the program, when run by a processor, controls the device where the storage medium is located to execute the method of the present invention.

[0015] According to another aspect of the present invention, a processor is also provided for running a program, wherein the program executes the methods of the present invention during runtime.

[0016] According to another aspect of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the method of the present invention.

[0017] According to another aspect of the present invention, an electronic device is also provided, comprising a processor and a memory for storing processor-executable instructions. The processor is configured to execute instructions to implement the methods of the embodiments of the present invention.

[0018] In this embodiment of the invention, an initial wiring path in a power distribution expansion scenario and multiple initial trajectory points on the initial wiring path are obtained; the multiple initial trajectory points are filtered according to a filtering strategy to obtain at least one target trajectory point, wherein the filtering strategy is used to characterize the rules for filtering noise points present in the multiple initial trajectory points; based on the at least one target trajectory point, multiple key trajectory points are determined, wherein the importance of key trajectory points in the initial wiring path is higher than the importance of target trajectory points; based on the multiple key trajectory points, a target wiring path is generated, and based on the target wiring path, a target wiring distance in the power distribution expansion scenario is determined; based on the target wiring distance and the target wiring path, wiring materials are predicted in the power distribution expansion scenario to obtain wiring material information. In other words, the embodiments of the present invention can first obtain the initial wiring path in the power distribution expansion scenario, as well as multiple initial trajectory points on the initial wiring path. Then, according to the rule of filtering noise points in the multiple initial trajectory points, the multiple initial trajectory points are filtered to obtain at least one target trajectory point. Then, based on the at least one target trajectory point, multiple key trajectory points can be determined. Based on the multiple key trajectory points obtained above, a target wiring path is generated. Based on the target wiring path, the target wiring distance in the power distribution expansion scenario can be determined. Finally, based on the target wiring distance and target wiring path obtained above, the wiring materials are predicted to achieve the purpose of obtaining wiring material information. Since multiple initial trajectory points are filtered after obtaining the initial wiring path and multiple initial trajectory points on the initial wiring path, multiple target trajectory points can be obtained. From these multiple target trajectory points, multiple key trajectory points can be determined. Using these multiple key trajectory points, a target wiring path can be generated. Furthermore, the target wiring distance can be determined based on the target wiring path. Based on the target wiring distance and target wiring path obtained above, the wiring material requirements in the current power distribution expansion scenario can be predicted to obtain wiring material information. This solves the technical problem of low prediction accuracy of wiring material information and achieves the technical effect of improving the prediction accuracy of wiring material information. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0020] Figure 1 This is a flowchart of a method for predicting wiring material information according to an embodiment of the present invention;

[0021] Figure 2 This is a flowchart of a method for obtaining filtered trajectory points according to an embodiment of the present invention;

[0022] Figure 3 This is a flowchart of a method for obtaining key trajectory points according to an embodiment of the present invention;

[0023] Figure 4 This is a flowchart of a wiring path generation method according to an embodiment of the present invention;

[0024] Figure 5 This is a flowchart of a method for estimating wiring material information according to an embodiment of the present invention;

[0025] Figure 6 This is a schematic diagram of a device for predicting wiring material information according to an embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] According to an embodiment of the present invention, a method for predicting wiring material information is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] The following describes the method for predicting wiring material information according to an embodiment of the present invention.

[0030] Figure 1 This is a flowchart of a method for predicting wiring material usage information according to an embodiment of the present invention, such as... Figure 1 As shown, the method for predicting wiring material usage information may include the following steps:

[0031] Step S101: Obtain the initial wiring path in the power distribution expansion scenario, as well as multiple initial trajectory points on the initial wiring path.

[0032] In the technical solution provided in step S101 of the present invention, a GPS recording instrument can be used to obtain the initial wiring path in a power distribution expansion scenario, as well as multiple initial trajectory points on the initial wiring path. These multiple initial trajectory points include the start and end points of the initial wiring path, and the start and end points are respectively the points accessed by pressing the start and end buttons on a GPS handheld device.

[0033] For example, during low-voltage business expansion surveys, surveyors use GPS recording devices to walk the wiring route and obtain several track points, simultaneously determining the start and end points, which are the start and end points indicated by the GPS handheld device. Low-voltage business expansion refers to the expansion or renovation of low-voltage power distribution networks, mainly involving the addition or replacement of low-voltage cables, wires, transformers, and other equipment to meet user electricity demands or improve power grid quality.

[0034] Furthermore, assuming there are a total of N trajectory points, the resulting set of data can be sorted in chronological order, i.e.: (P1, P2, ..., P... N ), where P1 represents the starting point of the trajectory point, P N This is used to represent the endpoint of a trajectory point. Each trajectory point corresponds to a geographic location coordinate, that is, the geographic location coordinate of the i-th point can be represented as P. i =(x i y i It should be noted that this is only a preferred implementation method for obtaining multiple initial trajectory points, and the process and method for obtaining multiple initial trajectory points are not specifically limited.

[0035] Step S102: Filter multiple initial trajectory points according to the filtering strategy to obtain at least one target trajectory point.

[0036] In the technical solution provided by step S102 of the present invention, after obtaining multiple initial trajectory points, it is necessary to filter the multiple initial trajectory points according to a filtering strategy in order to obtain at least one target trajectory point. The filtering strategy is used to characterize the rules for filtering noise points present in the multiple initial trajectory points.

[0037] Optionally, an improved clustering algorithm (e.g., an improved DBSCAN clustering algorithm) in the trajectory point noise filtering module can be used to filter multiple initial trajectory points to obtain at least one target trajectory point. This achieves the goal of filtering out all points that meet the clustering conditions, and the remaining un-clustered points are identified as noise points. Compared to typical clustering algorithms (e.g., the DBSCAN algorithm), this approach does not require dividing coordinate information points into multiple clusters; instead, it only requires grouping all coordinate information points within a certain range of the actual trajectory into a single cluster.

[0038] It should be noted that this is only a preferred embodiment for obtaining at least one target trajectory point, and the process and method for obtaining at least one target trajectory point are not specifically limited. As long as the method and process of filtering multiple initial trajectory points according to the filtering strategy to obtain at least one target trajectory point are within the protection scope of this invention, they will not be listed here.

[0039] Step S103: Based on at least one target trajectory point, determine multiple key trajectory points.

[0040] In the technical solution provided by step s103 of the present invention, a wiring path key coordinate acquisition module is used to determine multiple key trajectory points from at least one target trajectory point. In the initial wiring path, the importance of the key trajectory points is higher than that of the target trajectory points.

[0041] Optionally, after the trajectory point noise filtering module obtains the trajectory point samples with filtered noise, it can find the key trajectory points that can represent the wiring path from the trajectory point samples with filtered noise.

[0042] Optionally, based on at least one target trajectory point and the position coordinates corresponding to at least one target trajectory point, the position coordinates of key trajectory points can be determined, thereby achieving the purpose of determining multiple key trajectory points.

[0043] For example, after obtaining N trajectory points and a corresponding geographic coordinate for each trajectory point, a parameter K can be set, and the geographic coordinates of key trajectory points can be obtained from the first K coordinates of the geographic coordinates of multiple trajectory points, thereby determining multiple key trajectory points.

[0044] It should be noted that this is only a preferred embodiment for determining multiple key trajectory points, and the process and method for determining multiple key trajectory points are not specifically limited. As long as it is based on at least one target trajectory point, the process and method for determining multiple key trajectory points are within the protection scope of this invention, and will not be listed here.

[0045] Step S104: Generate a target wiring path based on multiple key trajectory points, and determine the target wiring distance in the power distribution expansion scenario based on the target wiring path.

[0046] In the technical solution provided by step S104 of the present invention, a target wiring path can be generated based on the obtained multiple key trajectory points, and then the target wiring distance in the power distribution expansion scenario can be determined based on the obtained target wiring path.

[0047] Optionally, by connecting multiple key trajectory points obtained using the wiring path designation module, the target wiring path can be obtained. Measuring the target wiring path yields the target wiring distance in the power distribution expansion scenario. Here, the target wiring path can be the final wiring path, and the target wiring distance can be the final total wiring distance.

[0048] For example, in the critical coordinate acquisition module of the cabling path, the critical trajectory points among the first K trajectory points can be obtained. In the cabling path determination module, the first K trajectory points are removed from the original trajectory point set, and then the critical trajectory points are used as new starting points. The critical coordinate acquisition module of the cabling path is used again to obtain the critical trajectory points one by one. The trajectory starting points of the original trajectory points are connected according to the critical trajectory points generated before and after time until they are connected to the endpoint. Finally, the distances of each line segment are added together to obtain the total distance of the cabling line.

[0049] It should be noted that this is only a preferred embodiment for determining the target wiring distance in a power distribution expansion scenario. The process and method for determining the target wiring distance in a power distribution expansion scenario are not specifically limited. As long as the target wiring path is generated based on multiple key trajectory points, and the process and method for determining the target wiring distance in a power distribution expansion scenario based on the target wiring path are within the protection scope of this invention, they will not be listed here.

[0050] Step S105: Based on the target wiring distance and target wiring path, predict the wiring materials required in the power distribution expansion scenario to obtain wiring material information.

[0051] In the technical solution provided by step S105 of the present invention, based on the obtained target wiring distance and target wiring path, the wiring material estimation module can predict the wiring material in the power distribution expansion scenario so as to obtain wiring material information.

[0052] Optionally, the wiring material information may include pole and tower material information, insulator material information, and line material information. Pole and tower material information describes the material usage of poles and towers and can be referred to as total pole and tower material usage. Insulator material information describes the installation location and quantity of insulators and can be referred to as total insulator material usage. Line material information can be referred to as total line material usage.

[0053] For example, after obtaining the target wiring distance and target wiring path using the wiring path planning module, the wiring material estimation module can be used to calculate the wiring material information required for low-voltage business expansion, as well as its total wiring distance. The wiring material information includes the total material usage for the line, the total material usage for the poles and towers, and the total material usage for the insulators.

[0054] It is understood that this is only a preferred implementation method for obtaining wiring material information in the power distribution expansion scenario. The process and method for obtaining wiring material information in the power distribution expansion scenario are not specifically limited. As long as the wiring material is predicted in the power distribution expansion scenario based on the target wiring distance and target wiring path, the process and method for obtaining wiring material information are within the protection scope of this invention, and will not be elaborated here.

[0055] In steps S101 to S105 of the present invention, the initial wiring path in the power distribution expansion scenario and multiple initial trajectory points on the initial wiring path are first obtained. Then, the multiple initial trajectory points are filtered according to the rules for filtering noise points present in the multiple initial trajectory points to obtain at least one target trajectory point. Then, based on the at least one target trajectory point, multiple key trajectory points can be determined. Based on the multiple key trajectory points obtained above, a target wiring path is generated. Based on the target wiring path, the target wiring distance in the power distribution expansion scenario can be determined. Finally, based on the target wiring distance and target wiring path obtained above, the wiring materials are predicted to achieve the purpose of obtaining wiring material information. Since multiple initial trajectory points are filtered after obtaining the initial wiring path and multiple initial trajectory points on the initial wiring path, multiple target trajectory points can be obtained. From these multiple target trajectory points, multiple key trajectory points can be determined. Using these multiple key trajectory points, a target wiring path can be generated. Furthermore, the target wiring distance can be determined based on the target wiring path. Based on the target wiring distance and target wiring path obtained above, the wiring material requirements in the current power distribution expansion scenario can be predicted to obtain wiring material information. This solves the technical problem of low prediction accuracy of wiring material information and achieves the technical effect of improving the prediction accuracy of wiring material information.

[0056] The method described in this embodiment will be further described below.

[0057] As an optional embodiment, filtering multiple initial trajectory points according to a filtering strategy to obtain at least one target trajectory point includes: obtaining the access status of the multiple initial trajectory points respectively; in response to the access status of a first trajectory point being unaccessed, obtaining a first distance between the first trajectory point and a second trajectory point, wherein the first trajectory point is any point among the multiple initial trajectory points, and the second trajectory point is any point among the multiple initial trajectory points other than the first trajectory point; in response to the first distance being less than a first distance threshold, determining a neighborhood set of the first trajectory point; in response to the number of elements in the neighborhood set being greater than or equal to the number of target elements, determining the first trajectory point as a target trajectory point, and updating the access status of the first trajectory point to an accessed state; and determining multiple target trajectory points based on the updated access status of the multiple initial trajectory points.

[0058] In this embodiment, after obtaining multiple initial trajectory points, a trajectory point noise filtering module is used to treat these initial trajectory points as a sample set. The access status of each initial trajectory point is then obtained. If any trajectory point is selected from the multiple initial trajectory points as the first trajectory point, and its access status is unaccessed, a first distance is obtained between the first trajectory point and a second trajectory point selected from the multiple trajectory points (excluding the first trajectory point). This first distance is compared with a first distance threshold. If the first distance is less than the first distance threshold, a neighborhood set of the first trajectory point is determined. If the number of elements in the neighborhood set is greater than or equal to the number of target elements, the first trajectory point is determined as the target trajectory point, and its access status is updated to accessed. This process is repeated until all initial trajectory points are in the accessed state, at which point the loop stops. This indicates that each of the multiple initial trajectory points has been filtered, thus enabling the determination of multiple target trajectory points.

[0059] Optionally, when the first trajectory point passes through p a The second trajectory point is represented by p. b When representing the distance, the first distance can be obtained through d. a，b This is represented. The first distance threshold can be a preset value and is represented by the parameter ε. When the first trajectory point can be reached through p... x When representing, the neighborhood set can be represented by the ε-neighborhood subset N. ε (p x The target element count can be a preset value, represented by minPts. The target trajectory points can be called core points.

[0060] For example, the process of determining multiple target trajectory points using the trajectory point noise filtering module described above can be as follows: All trajectory points are treated as a sample set, and the access status of all samples is marked as unvisited. Then, each sample is traversed. At the start of the main traversal, it is first necessary to determine whether the sample has been visited. If the sample has been visited, the traversal of the next sample begins; if the sample has not been visited, its access status is marked as unvisited. Then, it is determined whether the current sample is a core point. In this embodiment, d is used. a，b p a to p b The Euclidean distance is given by the following formula:

[0061]

[0062] In the above formula, p a Used to represent any point in the sample set, where the coordinates of that point are (x, y). a y a p b Used to represent the sample set except for p a any point other than (x, y), and the coordinates of that point are (x, y). b y b At this point, after obtaining the distance d... a，b Then, if the distance satisfies the following formula, then p is considered to be... a In p b Within the neighborhood of p, at the same time b Also in p a Within its neighborhood:

[0063] d a，b <ε

[0064] In the above formula, the parameter ε is used to characterize the distance threshold between samples, and then p can be found according to the above formula. x ε-neighborhood subset N ε (p x If the condition for determining the core point is as shown in the following formula:

[0065] N ε (p x )≥minPts

[0066] In the above formula, minPts is used to represent the threshold number of samples in the neighborhood of each sample. If the trajectory point p x If the ε-neighborhood subset satisfies the above formula, then p is considered to be... x This is the core point. It's important to note that ε and minPts are crucial adjustment parameters in this module, directly affecting the effectiveness and intensity of noise filtering.

[0067] Furthermore, based on the above process, we can continue to determine whether the current sample is a core point. If it is not a core point, we begin traversing the next sample. If it is a core point, we add that point to the target cluster (cluster C) and obtain the set of all samples in its neighborhood. This sample set can be represented by N. We traverse each sample in N again, marking the traversed samples as visited and adding them to cluster C. If a sample is found to be a core point during this traversal, we add all samples in its neighborhood to set N. This process continues until all samples in set N have been visited, then we return to the main traversal. When all samples in the sample set have been visited, the algorithm terminates. Through this module, we can finally obtain a cluster C. The core points obtained by filtering all samples, along with the coordinates of the core points, form the noise-filtered trajectory geographic coordinate information, which is input into the wiring path key coordinate acquisition module for processing.

[0068] As an optional embodiment, determining multiple key trajectory points based on at least one target trajectory point includes: selecting a target number of trajectory points from the multiple target trajectory points; generating a target number of trajectory groups based on the target number of trajectory points; obtaining the centroid coordinates of each target number of trajectory groups and the centroid points corresponding to the centroid coordinates; connecting each target number of centroid points to a starting point to generate a target number of target straight lines, wherein the starting point is obtained by selecting from multiple initial trajectory points; and determining multiple key trajectory points based on the target number of target straight lines.

[0069] In this embodiment, by using the wiring path key coordinate acquisition module, a number of target trajectory points can be selected from multiple target trajectory points. Then, a number of target trajectory groups can be generated based on the number of target trajectory points. The centroid coordinates of the target trajectory groups and the centroid points corresponding to the centroid coordinates are then obtained. Furthermore, the centroid points of the target groups are connected to the starting point to generate a number of target straight lines. Finally, based on the target straight lines obtained above, the purpose of determining multiple key trajectory points can be achieved.

[0070] Optionally, the target value can be a preset value and can be represented by the parameter K. Then, K trajectory points can be selected from multiple target trajectory points. These K trajectory points can be selected via (P1, P2, ..., P...). k The data can be represented as follows: Based on K trajectory points, generate K trajectory groups. These K groups can be represented by (P1), (P1, P2), (P1, P2, P3), ..., (P1, P2, ..., P...). k This is represented by ); then the centroid coordinates of K trajectory groups are obtained respectively. The K centroid coordinates can be represented by Q1, Q2, Q3, ..., Q kAfter representing the target line and identifying the centroid points corresponding to the centroid coordinates, connect the K centroid points to the starting point to generate K target lines. These K target lines can then pass through l1, l2…l k To express.

[0071] For example, the process of determining multiple key trajectory points using the wiring path key coordinate acquisition module is as follows. First, a parameter K is set. Based on the first K points in the trajectory point sample set with filtered noise obtained by the trajectory point noise filtering module, K trajectory groups are generated, namely (P1), (P1, P2), (P1, P2, P3), ..., (P1, P2, ..., P2). k Then, calculate the centroid coordinates of these K sets of points, obtaining K centroid coordinates: Q1, Q2, Q3, ..., Q... k Among them, the calculation of the point set (P1, P2…P) i The center of gravity Q i The coordinates are shown in the following formula:

[0072]

[0073] In the above formula, i represents the number of trajectory points in the point set, and x gi Used to represent the centroid coordinate Q i x-coordinate, y-coordinate gi Used to represent the centroid coordinate Q i The y-coordinate of the trajectory is determined. Then, connecting the starting point of the trajectory with the K centroid coordinates yields K straight lines, namely l1, l2…l… k Assume the i-th line l i The equation is shown below:

[0074] l i A i X+B i Y+C i =0

[0075] In the above formula, A i B i C i These are all used to represent the coefficients of the i-th line, and their specific values ​​are as follows:

[0076]

[0077] After obtaining K target straight lines according to the above process, multiple key trajectory points can be determined.

[0078] As an optional implementation method, multiple key trajectory points are determined based on the target numerical line, including: obtaining the second distance between the trajectory points in the trajectory group and the target line respectively; summing the multiple second distances to obtain the target sum value; and determining multiple key trajectory points based on the multiple target sum values.

[0079] In this embodiment, the wiring path key coordinate acquisition module is used to obtain the second distance between the trajectory point in the trajectory group and the target line based on the obtained target value and target line. Then, the summation of multiple second distances can be performed to obtain the target sum value. After obtaining multiple target sum values ​​according to the above process, the minimum sum value is selected from the multiple target sum values, and then multiple key trajectory points are determined based on the minimum sum value.

[0080] Optionally, any trajectory point can be selected from the trajectory group, and this trajectory point can be accessed via P. i To represent this, the target line can be represented by l. j If represented, then the trajectory point P i With the target line l j The second distance between them can be obtained by d i，j The target and value corresponding to the j-th target line can be represented by D. j To express.

[0081] For example, after obtaining K straight lines using the critical coordinate acquisition module for wiring paths, the sum of the distances from the P trajectories contained in the P point set to each straight line is calculated. Then, the distance from the P trajectories to the straight line l is... j The sum of the distances can be calculated using the following formula:

[0082]

[0083] Where, d i，j Used to represent trajectory point P i With line l j The distance to the i-th trajectory point P i to the j-th straight line l j The distance can be calculated using the following formula:

[0084]

[0085] Next, find the minimum value among the sum of the distances from the trajectory points to the straight lines. The calculation formula is shown below:

[0086] D min =min(D1, D2, D3, ..., D k )

[0087] From the above formula, we can find the centroid coordinates corresponding to the minimum sum of distances. Let's assume these centroid coordinates are Q.i So Q i A key trajectory point is a point on the wiring path. Based on the above process, multiple key trajectory points can be determined and then input into the wiring path specification module for further processing.

[0088] As an optional implementation method, a target wiring path is generated based on multiple key trajectory points, and a target wiring distance is determined based on the target wiring path in the power distribution expansion scenario, including: obtaining the timestamps of multiple key trajectory points respectively; sorting the multiple key trajectory points based on the multiple timestamps to obtain sorted multiple key trajectory points; and obtaining the target wiring distance and target wiring path based on the sorted multiple key trajectory points.

[0089] In this embodiment, the wiring path determination module can obtain the timestamps of multiple key trajectory points, and then sort the multiple key trajectory points according to the multiple timestamps obtained above to obtain sorted multiple key trajectory points. Furthermore, based on the sorted multiple key trajectory points, the target wiring distance and the target wiring path can be obtained.

[0090] For example, after obtaining the timestamps of multiple key trajectory points, the multiple key trajectory points are sorted in chronological order. Then, the sorted multiple key trajectory points can be connected in sequence to obtain the target wiring path. Based on the target wiring path, the target wiring distance can be determined.

[0091] As an optional implementation, the target wiring distance and target wiring path are obtained based on multiple sorted key trajectory points, including: connecting the multiple sorted key trajectory points to obtain the target wiring path; determining multiple third distances based on the target wiring path; and summing the multiple third distances to obtain the target wiring distance.

[0092] In this embodiment, a wiring path determination module connects multiple sorted key trajectory points to obtain a target wiring path. Based on the obtained target wiring path, multiple third distances are determined, and then the summation of these third distances is performed to obtain the target wiring distance. The third distance can be any distance between adjacent key trajectory points, and can be determined by S. i，i+1 This can be represented. The target wiring distance can be expressed using D. 总 To express.

[0093] For example, the process of obtaining the target wiring distance using the wiring path determination module is as follows: First, the wiring path critical coordinate acquisition module is used to obtain all critical trajectory points, which are placed in a set E. Then, they are sorted by timestamp, and the condition for determining whether a point is the last critical trajectory point is that the number of remaining trajectory points is less than K. Next, the starting point is connected to the first obtained critical trajectory point, and then all critical trajectory points are connected sequentially according to their timestamps until the endpoint is reached, thus determining the total wiring distance. The distance between critical trajectory points can be expressed by the following formula:

[0094]

[0095] In the above formula, S i，i+1 This represents the distance between the (i+1)th key trajectory point and the ith key trajectory point. Then, the distance for each line segment is calculated sequentially, and all distances are summed to obtain the total cabling distance. The formula for calculating the total cabling distance is as follows:

[0096]

[0097] In the above formula, M represents the total number of paths on the outdoor cabling route, and D... 总 This is used to represent the total wiring distance. Finally, the total wiring distance and the set of key trajectory points E are input into the wiring material estimation module for further processing.

[0098] As an optional implementation method, based on the target wiring distance and the target wiring path, the wiring material usage is predicted in the power distribution expansion scenario to obtain wiring material information, including: determining the pole and tower material information in the wiring material information based on the target wiring path; determining the insulator material information in the wiring material information based on the pole and tower material information; and determining the line material information in the wiring material information based on the target wiring distance.

[0099] In this embodiment, the wiring material estimation module can be used to determine the pole and tower material information in the wiring material information based on the obtained target wiring path. Then, based on the obtained pole and tower material information, the insulator material information can be determined. Based on the obtained target wiring distance, the purpose of determining the line material information can be achieved.

[0100] Optionally, the target wiring distance and the tilt influence coefficient are multiplied to obtain the target product, and the wiring material information is determined based on the target product.

[0101] For example, the process of obtaining wiring material estimation information based on the target wiring distance and target wiring path using the wiring material estimation module is as follows. First, a pole is placed for all samples in the obtained sample set E, and another pole is placed at certain intervals within the sub-segment. Finally, the total number of poles required in the power distribution expansion scenario is determined, which can be expressed by the following formula:

[0102]

[0103] In the above formula, h represents the total number of towers required, α represents the spacing between towers, and the ceil() function is used to round the value up. After obtaining the number of towers, a fixed number of insulators need to be installed on each tower. This allows us to obtain the total number of insulators required in the power distribution expansion scenario, which can be expressed by the following formula:

[0104] q=λh

[0105] In the above formula, q represents the total number of insulators, and λ represents the number of insulators required on each tower. Finally, based on the total line distance D_total output by the wiring path determination module, the total amount of materials required for the line can be determined, as shown in the following formula:

[0106] u=D 总 ×4×u(1<u<1.1)

[0107] Where u represents the total amount of material used in the line, and μ represents the tilt influence coefficient of the line material. Since the line itself has a certain weight, it will usually bend to a certain extent under the influence of gravity. Therefore, a tilt influence coefficient is considered to be multiplied by the total length. At the same time, a three-phase four-wire system is considered, with each tower connected by four lines, in order to calculate the total amount of material used in the line.

[0108] In this embodiment, the initial wiring path in the power distribution expansion scenario and multiple initial trajectory points on the initial wiring path can be obtained first. Then, according to the rule of filtering noise points in the multiple initial trajectory points, the multiple initial trajectory points are filtered to obtain at least one target trajectory point. Then, based on the at least one target trajectory point, multiple key trajectory points can be determined. Based on the multiple key trajectory points obtained above, a target wiring path is generated. Based on the target wiring path, the target wiring distance in the power distribution expansion scenario can be determined. Finally, based on the target wiring distance and target wiring path obtained above, the wiring materials are predicted to achieve the purpose of obtaining wiring material information. Since multiple initial trajectory points are filtered after obtaining the initial wiring path and multiple initial trajectory points on the initial wiring path, multiple target trajectory points can be obtained. From these multiple target trajectory points, multiple key trajectory points can be determined. Using these multiple key trajectory points, a target wiring path can be generated. Furthermore, the target wiring distance can be determined based on the target wiring path. Based on the target wiring distance and target wiring path obtained above, the wiring material requirements in the current power distribution expansion scenario can be predicted to obtain wiring material information. This solves the technical problem of low prediction accuracy of wiring material information and achieves the technical effect of improving the prediction accuracy of wiring material information.

[0109] The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.

[0110] When power companies conduct low-voltage expansion site surveys, traditional outdoor site surveys rely on manual observation and recording. This involves estimating the route and length of the line through on-site assessment and observation, and further estimating the materials required for the expansion line. This reliance on manual labor leads to problems such as untimely data updates and inefficient resource allocation for the power grid. To address these issues, it is necessary to develop digital methods for low-voltage expansion site surveys within the context of the power industry's digitalization process. A common approach is to use GPS systems, where staff use handheld GPS devices to survey the low-voltage distribution expansion site, obtaining location points and thus information such as wiring material requirements. However, this method is susceptible to noise interference when using GPS to obtain location points, leading to inaccuracies in the obtained points and resulting in low accuracy in predicting wiring material requirements.

[0111] Therefore, in order to solve the above problems, this invention proposes a low-voltage business expansion outdoor cabling survey method based on GPS system. The method first uses GPS positioning equipment to collect the required trajectory points on the cabling path and simultaneously determines the starting point and the ending point. Then, the GPS trajectory points are filtered for noise using a DBSCAN-based trajectory noise filtering module. After obtaining the filtered trajectory points, the first step is to set up K sets of trajectory points based on the first K trajectory points. The second step is to calculate the centroid coordinates Q of the K sets of points respectively. The third step is to connect the starting point to all centroids Q to obtain K sets of straight lines. Then, calculate the distance from the first K trajectory points to each straight line, compare them to find the shortest distance, and use the centroid of the straight line corresponding to this distance as a point on the line. Connect this point to the starting point and use this point as the new starting point. After removing the first K trajectory points from the point set, repeat the third step until it is connected to the final endpoint to obtain the final wiring path. Based on the final wiring path obtained above, the wiring material estimation module is used to obtain the wiring material information required for low-voltage business expansion, thereby solving the technical problem of low prediction accuracy of wiring material information and achieving the technical effect of improving the prediction accuracy of wiring material information.

[0112] In this embodiment, during low-voltage business expansion surveys, surveyors can use a GPS recording device to traverse the cabling route and obtain all GPS trajectory points along the route. Then, a trajectory point noise filtering module filters the obtained trajectory points for noise. Next, a cabling path key coordinate acquisition module acquires the key trajectory points from the noise-filtered points. Subsequently, a cabling path planning module connects the starting point with the sequentially acquired key trajectory points until the endpoint is reached, thus obtaining the optimized cabling path. Finally, a cabling material estimation module estimates the required cabling materials.

[0113] Figure 2 This is a flowchart of a method for obtaining filtered trajectory points according to an embodiment of the present invention, as follows: Figure 2 As shown, this method can be used in the trajectory point noise filtering module to obtain filtered trajectory points. The above method for obtaining filtered trajectory points mainly includes the following steps:

[0114] Step S201: Collect track points using a GPS device.

[0115] In this embodiment, trajectory points are collected via GPS devices in the trajectory point noise filtering module. Within this module, an improved DBSCAN clustering algorithm is used to filter multiple initial trajectory points, resulting in at least one target trajectory point. This process filters out all points that meet the clustering criteria, leaving only the un-clustered points as noise points. Compared to the typical DBSCAN algorithm, this approach eliminates the need to divide coordinate information points into multiple clusters; instead, it suffices to group all coordinate information points within a certain range of the actual trajectory into a single cluster.

[0116] Optionally, during low-voltage business expansion surveys, surveyors use GPS recording devices to walk the wiring route to obtain several trajectory points, simultaneously determining the start and end points. Assuming there are N trajectory points in total, the resulting data can be sorted chronologically as: (P1, P2, ..., P...). N ), where P1 represents the starting point of the trajectory point, P N This is used to represent the endpoint of a trajectory point. Each trajectory point corresponds to a geographic location coordinate, that is, the geographic location coordinate of the i-th point can be represented as P. i =(x i y i ).

[0117] Step S202: Select unvisited trajectory points.

[0118] Step S203: Determine whether the input trajectory point is a core point.

[0119] In this embodiment, it can be determined whether the input trajectory point is a core point. If it is, step S204 is executed; otherwise, step S207 is executed.

[0120] In this embodiment, all trajectory points are treated as a sample set. The access status of all samples is then marked as unvisited, and traversal of each sample begins. At the start of the main traversal, it is first necessary to determine whether the sample has been visited. If the sample has been visited, the traversal of the next sample begins; if the sample has not been visited, its access status is marked as unvisited. Then, it is determined whether the current sample is a core point. In this embodiment, d is used... a，b p a to p b The Euclidean distance is given by the following formula:

[0121]

[0122] In the above formula, p a Used to represent any point in the sample set, where the coordinates of that point are (x, y). a y a pb Used to represent the sample set except for p a any point other than (x, y), and the coordinates of that point are (x, y). b y b At this point, after obtaining the distance d... a，b Then, if the distance satisfies the following formula, then p is considered to be... a In p b Within the neighborhood of p, at the same time b Also in p a Within its neighborhood:

[0123] d a，b <ε

[0124] Here, the parameter ε is used to characterize the distance threshold between samples, and p can be found according to the above formula. x ε-neighborhood subset N ε (p x If the condition for determining the core point is as shown in the following formula:

[0125] N ε (p x )≥minPts

[0126] In the above formula, minPts is used to represent the threshold number of samples in the neighborhood of each sample. If the trajectory point p x If the ε-neighborhood subset satisfies the above formula, then p is considered to be... x This is the core point. It's important to note that ε and minPts are crucial adjustment parameters in this module, directly affecting the effectiveness and intensity of noise filtering.

[0127] Optionally, if the above conditions are met, the core point is retained; otherwise, the point is marked as a noise point.

[0128] Step S204: Retain the core points.

[0129] Step S205: Determine if there are any unprocessed points.

[0130] In this embodiment, it is necessary to determine whether there are any unprocessed points. If so, step S207 is executed; otherwise, step S206 is executed.

[0131] Step S206: Filtered trajectory points.

[0132] Step S207: Mark as noise points.

[0133] In this embodiment, based on the above process, it can be further determined whether the current sample is a core point. If it is not a core point, the traversal of the next sample begins. If it is a core point, the point is added to cluster C, and the set of all samples in the neighborhood of the sample is obtained. This sample set can be represented by N. Each sample in N is traversed again, and the traversed sample is marked as visited, and the sample is also added to cluster C. If a sample is found to be a core point during this traversal, all samples in the neighborhood of that sample are added to set N. This process continues until all samples in set N have been visited, then the main traversal is returned. When all samples in the sample set have been visited, the algorithm terminates. Through this module, a cluster C can be obtained. The core points obtained by filtering all samples, and the coordinates of the core points, constitute the noise-filtered trajectory geographic coordinate information, which is input to the wiring path key coordinate acquisition module for processing.

[0134] Figure 3 This is a flowchart of a method for obtaining key trajectory points according to an embodiment of the present invention. Based on Figure 2 The flowchart illustrates how, after obtaining filtered trajectory points in the trajectory point noise filtering module, these filtered trajectory points are input into the wiring path critical coordinate acquisition module to obtain critical trajectory points, as shown below. Figure 3 As shown, the main steps include the following:

[0135] Step S301: Determine the starting point and ending point of the trajectory.

[0136] Step S302: Generate K sets of trajectory groups based on the first K trajectory points.

[0137] In this embodiment, a parameter K is set. Based on the first K points in the trajectory point sample set with filtered noise obtained by the trajectory point noise filtering module, K trajectory groups are generated, namely (P1), (P1, P2), (P1, P2, P3), ..., (P1, P2, ..., P2). k ).

[0138] Step S303: Determine the centroid coordinates of the K trajectory groups respectively.

[0139] In this embodiment, based on K sets of trajectories, the centroid coordinates of these K sets of points are calculated respectively, resulting in K centroid coordinates: Q1, Q2, Q3, ..., Q k Among them, the calculation of the point set (P1, P2…P) i The center of gravity Q i The coordinates are shown in the following formula:

[0140]

[0141] In the above formula, i represents the number of trajectory points in the point set, and xgi Used to represent the centroid coordinate Q i x-coordinate, y-coordinate gi Used to represent the centroid coordinate Q i The y-coordinate.

[0142] Step S304: Connect the starting point and the K centroid coordinates with K straight lines.

[0143] In this embodiment, connecting the starting point of the trajectory with K centroid coordinates yields K straight lines, namely l1, l2…l k Assume the i-th line l i The equation is shown below:

[0144] l i A i X+B i Y+C i =0

[0145] In the above formula, A i B i C i These are all used to represent the coefficients of the i-th line, and their specific values ​​are as follows:

[0146]

[0147] Based on the above process, K target straight lines can be obtained.

[0148] Step S305: Calculate the distances from the K trajectory points to all straight lines.

[0149] In this embodiment, after obtaining K straight lines using the wiring path critical coordinate acquisition module, the sum of the distances from the P trajectories contained in the P point set to each straight line is calculated. Then, the distance from the P trajectories to straight line l is... j The sum of the distances can be calculated using the following formula:

[0150]

[0151] Where, d i，j Used to represent trajectory point P i With line l j The distance to the i-th trajectory point P i to the j-th straight line l j The distance can be calculated using the following formula:

[0152]

[0153] Next, find the minimum value among the sum of the distances from the trajectory points to the straight lines. The calculation formula is shown below:

[0154] D min=min(D1, D2, D3, ..., D k )

[0155] As can be seen from the above formula, the centroid coordinates corresponding to the minimum sum of distances can be found.

[0156] Step S306: Determine multiple key trajectory points.

[0157] In this embodiment, the centroid coordinates corresponding to the minimum sum of distances from the trajectory points to the straight lines can be found. Let's assume that the centroid coordinates are Q. i So Q i A key trajectory point is a point on the wiring path. Based on the above process, multiple key trajectory points can be determined and then input into the wiring path specification module for further processing.

[0158] Figure 4 This is a flowchart of a wiring path generation method according to an embodiment of the present invention. Based on Figure 3 The flowchart illustrates how, after determining multiple key trajectory points in the wiring path key coordinate acquisition module, these points are input into the wiring path specification module to generate the wiring path. Figure 4 As shown, the main steps include the following:

[0159] Step S401: Select the starting point from the multiple key trajectory points obtained.

[0160] Step S402: Connect the starting point and multiple key trajectory points sequentially until the endpoint is reached to generate the wiring path.

[0161] Step S403: Calculate the total cabling distance based on the cabling path.

[0162] In this embodiment, the critical coordinate acquisition module for the wiring path is first used to obtain all critical trajectory points, which are then placed in a set E. These points are then sorted by timestamp, with the condition that the number of remaining trajectory points is less than K used to determine if a point is the final critical trajectory point. Next, the starting point is connected to the first obtained critical trajectory point, and then all critical trajectory points are connected sequentially according to their timestamps until the endpoint is reached, thus determining the total wiring distance. The distance between critical trajectory points can be expressed by the following formula:

[0163]

[0164] In the above formula, s i，i+1This represents the distance between the (i+1)th key trajectory point and the ith key trajectory point. Then, the distance for each line segment is calculated sequentially, and all distances are summed to obtain the total cabling distance. The formula for calculating the total cabling distance is as follows:

[0165]

[0166] Where M represents the total number of paths on the outdoor cabling route, and D... 总 This is used to represent the total wiring distance. Finally, the total wiring distance and the set of key trajectory points E are input into the wiring material estimation module for further processing.

[0167] In this embodiment, the critical coordinate acquisition module of the wiring path can obtain the critical trajectory points among the first K trajectory points. In the wiring path determination module, the first K trajectory points are removed from the original trajectory point set, and then the critical trajectory points are used as new starting points. The critical coordinate acquisition module of the wiring path is used again to obtain the critical trajectory points one by one. The trajectory starting points of the original trajectory points are connected according to the critical trajectory points generated before and after time until they are connected to the endpoint. Finally, the distances of each line segment are added together to obtain the total distance of the wiring line.

[0168] Figure 5 This is a flowchart of a method for estimating wiring material usage information according to an embodiment of the present invention. Based on Figure 4 The flowchart illustrates how, after generating the wiring path in the wiring path designation module, the wiring path is input into the wiring material estimation module to estimate wiring material usage information, i.e., as shown... Figure 5 As shown, the main steps include the following:

[0169] Step S501: Estimate the total amount of materials needed for the circuit.

[0170] In this embodiment, a pole is deployed for all samples in the obtained sample set E, and a pole is deployed at regular intervals within the sub-segment. The total number of poles required in the power distribution expansion scenario is then determined, which can be expressed by the following formula:

[0171]

[0172] In the above formula, h represents the total number of towers required, α represents the spacing between towers, and the ceil() function is used to round the value up.

[0173] Step S502: Estimate the total amount of material needed for the tower.

[0174] In this embodiment, after obtaining the number of towers, a fixed number of insulators need to be installed on each tower. This allows us to obtain the total number of insulators required for the power distribution expansion scenario, which can be expressed by the following formula:

[0175] q=λh

[0176] In the above formula, q represents the total number of insulators, and λ represents the number of insulators required on each tower.

[0177] Step S503: Estimate the total amount of material needed for insulators.

[0178] In this embodiment, the total line distance D_total output by the wiring path determination module can be used to determine the total amount of wiring materials required, as shown in the following formula:

[0179] u=D 总 ×4×u(1<u<1.1)

[0180] Where u represents the total amount of material used in the line, and μ represents the tilt influence coefficient of the line material. Since the line itself has a certain weight, it will usually bend to a certain extent under the influence of gravity. Therefore, a tilt influence coefficient is considered to be multiplied by the total length. At the same time, a three-phase four-wire system is considered, with each tower connected by four lines, in order to calculate the total amount of material used in the line.

[0181] In this embodiment, the initial wiring path in the power distribution expansion scenario and multiple initial trajectory points on the initial wiring path can be obtained first. Then, according to the rule of filtering noise points in the multiple initial trajectory points, the multiple initial trajectory points are filtered to obtain at least one target trajectory point. Then, based on the at least one target trajectory point, multiple key trajectory points can be determined. Based on the multiple key trajectory points obtained above, a target wiring path is generated. Based on the target wiring path, the target wiring distance in the power distribution expansion scenario can be determined. Finally, based on the target wiring distance and target wiring path obtained above, the wiring materials are predicted to achieve the purpose of obtaining wiring material information. Since multiple initial trajectory points are filtered after obtaining the initial wiring path and multiple initial trajectory points on the initial wiring path, multiple target trajectory points can be obtained. From these multiple target trajectory points, multiple key trajectory points can be determined. Using these multiple key trajectory points, a target wiring path can be generated. Furthermore, the target wiring distance can be determined based on the target wiring path. Based on the target wiring distance and target wiring path obtained above, the wiring material requirements in the current power distribution expansion scenario can be predicted to obtain wiring material information. This solves the technical problem of low prediction accuracy of wiring material information and achieves the technical effect of improving the prediction accuracy of wiring material information.

[0182] According to an embodiment of the present invention, a device for predicting wiring material usage information is provided. It should be noted that this device for predicting wiring material usage information can be used to execute a method for predicting wiring material usage information as described in the embodiment.

[0183] Figure 6 This is a schematic diagram of a device for predicting wiring material usage information according to an embodiment of the present invention, such as... Figure 6 As shown, a device 600 for predicting wiring material information may include: a first acquisition unit 601, a filtering unit 602, a first determination unit 603, a second determination unit 604, and a second acquisition unit 605.

[0184] The first acquisition unit 601 is used to acquire the initial wiring path in the power distribution expansion scenario, as well as multiple initial trajectory points on the initial wiring path.

[0185] The filtering unit 602 is used to filter multiple initial trajectory points according to a filtering strategy to obtain at least one target trajectory point, wherein the filtering strategy is used to characterize the rules for filtering noise points present in the multiple initial trajectory points.

[0186] The first determining unit 603 is used to determine multiple key trajectory points based on at least one target trajectory point, wherein the importance of the key trajectory points is higher than that of the target trajectory points in the initial wiring path.

[0187] The second determining unit 604 is used to generate a target wiring path based on multiple key trajectory points, and to determine the target wiring distance in the power distribution expansion scenario based on the target wiring path.

[0188] The second acquisition unit 605 is used to predict the wiring materials required in a power distribution expansion scenario based on the target wiring distance and the target wiring path, and obtain wiring material information.

[0189] Optionally, the filtering unit 602 may include: a first acquisition module, configured to acquire the access status of multiple initial trajectory points respectively; a second acquisition module, configured to acquire a first distance between the first trajectory point and a second trajectory point in response to the access status of the first trajectory point being unaccessed, wherein the first trajectory point is any point among the multiple initial trajectory points, and the second trajectory point is any point among the multiple initial trajectory points other than the first trajectory point; a first determination module, configured to determine a neighborhood set of the first trajectory point in response to the first distance being less than a first distance threshold; a second determination module, configured to determine the first trajectory point as a target trajectory point and update the access status of the first trajectory point to an accessed state in response to the number of elements in the neighborhood set being greater than or equal to the number of target elements; and a third determination module, configured to determine multiple target trajectory points based on the updated access status of the multiple initial trajectory points.

[0190] Optionally, the first determining unit 603 may include: a selection module, used to select a target numerical number of trajectory points from a plurality of target trajectory points; a first generating module, used to generate a target numerical number of trajectory groups based on the target numerical number of trajectory points; a third obtaining module, used to obtain the centroid coordinates of the target numerical number of trajectory groups and the centroid points corresponding to the centroid coordinates; a second generating module, used to connect the target numerical number of centroid points to the starting point respectively to generate a target numerical number of target straight lines, wherein the starting point is obtained by selecting from a plurality of initial trajectory points; and a fourth determining module, used to determine a plurality of key trajectory points based on the target numerical number of target straight lines.

[0191] Optionally, the fourth determining module may include: a first obtaining submodule, used to obtain the second distance between the trajectory points in the trajectory group and the target line respectively; a second obtaining submodule, used to sum the multiple second distances to obtain the target sum value; and a first determining submodule, used to determine multiple key trajectory points based on the multiple target sum values.

[0192] Optionally, the second determining unit 604 may include: a fourth acquisition module, used to acquire the timestamps of multiple key trajectory points respectively; a sorting module, used to sort the multiple key trajectory points based on the multiple timestamps to obtain the sorted multiple key trajectory points; and a fifth acquisition module, used to obtain the target wiring distance and the target wiring path based on the sorted multiple key trajectory points.

[0193] Optionally, the fifth acquisition module may include: a third acquisition submodule, used to connect multiple sorted key trajectory points to obtain the target wiring path; a second determination submodule, used to determine multiple third distances based on the target wiring path; and a fourth acquisition submodule, used to sum the multiple third distances to obtain the target wiring distance.

[0194] Optionally, the second acquisition unit 605 may include: a fifth determining module, used to determine the pole and tower material information in the wiring material information based on the target wiring path; a sixth determining module, used to determine the insulator material information in the wiring material information based on the pole and tower material information; and a seventh determining module, used to determine the line material information in the wiring material information based on the target wiring distance.

[0195] In this embodiment, the first acquisition unit acquires the initial wiring path and multiple initial trajectory points on the initial wiring path in the power distribution expansion scenario; the filtering unit filters the multiple initial trajectory points according to a filtering strategy to obtain at least one target trajectory point, wherein the filtering strategy is used to characterize the rules for filtering noise points present in the multiple initial trajectory points; the first determination unit determines multiple key trajectory points based on the at least one target trajectory point, wherein the importance of key trajectory points is higher than that of target trajectory points in the initial wiring path; the second determination unit generates a target wiring path based on the multiple key trajectory points, and determines the target wiring distance in the power distribution expansion scenario based on the target wiring path; the second acquisition unit predicts the wiring materials required in the power distribution expansion scenario based on the target wiring distance and the target wiring path to obtain wiring material information, thereby solving the technical problem of low prediction accuracy of wiring material information and achieving the technical effect of improving the prediction accuracy of wiring material information.

[0196] According to an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is run by a processor, it controls the device where the readable storage medium is located to execute the wiring material prediction method in the embodiment.

[0197] According to an embodiment of the present invention, a processor is also provided for running a program, wherein the program executes the method for predicting wiring material information in the embodiment during runtime.

[0198] According to an embodiment of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the method for predicting wiring material information in the embodiments of the present invention.

[0199] According to embodiments of the present invention, an electronic device is also provided, comprising a processor and a memory for storing processor-executable instructions. The processor is configured to execute instructions to implement the wiring material prediction method of the embodiments of the present invention.

[0200] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0201] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0202] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed can be through some interfaces; the indirect coupling or communication connection of units or modules can be electrical or other forms.

[0203] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0204] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0205] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0206] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for predicting wiring material usage information, characterized in that, include: Obtain the initial wiring path in the power distribution expansion scenario, and multiple initial trajectory points on the initial wiring path; The multiple initial trajectory points are filtered according to the filtering strategy to obtain at least one target trajectory point, wherein the filtering strategy is used to characterize the rules for filtering noise points present in the multiple initial trajectory points. Based on at least one target trajectory point, multiple key trajectory points are determined, wherein, in the initial wiring path, the importance of the key trajectory points is higher than that of the target trajectory points; Based on multiple key trajectory points, a target wiring path is generated, and based on the target wiring path, the target wiring distance in the power distribution expansion scenario is determined. Based on the target wiring distance and the target wiring path, the wiring material usage is predicted in the power distribution expansion scenario to obtain wiring material information; The process of filtering multiple initial trajectory points according to a filtering strategy to obtain at least one target trajectory point includes: acquiring the access status of each of the multiple initial trajectory points; in response to a first trajectory point being in an unaccessed state, acquiring a first distance between the first trajectory point and a second trajectory point, wherein the first trajectory point is any point among the multiple initial trajectory points, and the second trajectory point is any point among the multiple initial trajectory points other than the first trajectory point; in response to a first distance being less than a first distance threshold, determining a neighborhood set of the first trajectory point; in response to a neighborhood set having an element count greater than or equal to a target element count, determining the first trajectory point as a target trajectory point and updating the access status of the first trajectory point to an accessed state; and determining multiple target trajectory points based on the updated access status of the multiple initial trajectory points. Based on at least one target trajectory point, determining multiple key trajectory points includes: selecting a target numerical number of trajectory points from the multiple target trajectory points; generating a target numerical number of trajectory groups based on the target numerical number of trajectory points; obtaining the centroid coordinates of the target numerical number of trajectory groups and the centroid points corresponding to the centroid coordinates; connecting the target numerical number of centroid points to the starting point to generate the target numerical number of target straight lines, wherein the starting point is obtained by selecting from the multiple initial trajectory points; and determining multiple key trajectory points based on the target numerical number of target straight lines. Based on the target numerical line, multiple key trajectory points are determined, including: obtaining the second distance between the trajectory points in the trajectory group and the target line; summing the multiple second distances to obtain the target sum value; and determining multiple key trajectory points based on the multiple target sum values.

2. The method according to claim 1, characterized in that, Based on multiple key trajectory points, a target wiring path is generated, and based on the target wiring path, the target wiring distance in the power distribution expansion scenario is determined, including: Obtain the timestamps of multiple key trajectory points respectively; Based on multiple timestamps, multiple key trajectory points are sorted to obtain multiple sorted key trajectory points; Based on the sorted multiple key trajectory points, the target wiring distance and the target wiring path are obtained.

3. The method according to claim 2, characterized in that, Based on the sorted multiple key trajectory points, the target wiring distance and the target wiring path are obtained, including: Connect the sorted key trajectory points to obtain the target wiring path; Based on the target wiring path, multiple third distances are determined; The target wiring distance is obtained by summing multiple third distances.

4. The method according to claim 1, characterized in that, Based on the target wiring distance and the target wiring path, the wiring material usage is predicted in the power distribution expansion scenario to obtain wiring material information, including: Based on the target wiring path, determine the pole and tower material information in the wiring material information; Based on the tower material information, determine the insulator material information in the wiring material information; Based on the target wiring distance, determine the line material information in the wiring material information.

5. A device for predicting wiring material usage information, characterized in that, include: The first acquisition unit is used to acquire the initial wiring path in the power distribution expansion scenario, and multiple initial trajectory points on the initial wiring path; A filtering unit is configured to filter multiple initial trajectory points according to a filtering strategy to obtain at least one target trajectory point, wherein the filtering strategy is used to characterize the rules for filtering noise points present in the multiple initial trajectory points. The first determining unit is configured to determine multiple key trajectory points based on at least one target trajectory point, wherein, in the initial wiring path, the importance of the key trajectory points is higher than the importance of the target trajectory points; The second determining unit is used to generate a target wiring path based on multiple key trajectory points, and to determine the target wiring distance in the power distribution expansion scenario based on the target wiring path. The second acquisition unit is used to predict the wiring materials required in the power distribution expansion scenario based on the target wiring distance and the target wiring path, and obtain wiring material information. The filtering unit is further configured to: acquire the access status of multiple initial trajectory points respectively; in response to the access status of a first trajectory point being unaccessed, acquire a first distance between the first trajectory point and a second trajectory point, wherein the first trajectory point is any point among the multiple initial trajectory points, and the second trajectory point is any point among the multiple initial trajectory points other than the first trajectory point; in response to the first distance being less than a first distance threshold, determine a neighborhood set of the first trajectory point; in response to the number of elements in the neighborhood set being greater than or equal to the number of target elements, determine the first trajectory point as a target trajectory point, and update the access status of the first trajectory point to an accessed state; and determine multiple target trajectory points based on the updated access status of the multiple initial trajectory points. The first determining unit is further configured to: select a target numerical number of trajectory points from a plurality of target trajectory points; generate a target numerical number of trajectory groups based on the target numerical number of trajectory points; obtain the centroid coordinates of the target numerical number of trajectory groups and the centroid points corresponding to the centroid coordinates; connect the target numerical number of centroid points to the starting point to generate the target numerical number of target straight lines, wherein the starting point is obtained by selecting from a plurality of initial trajectory points; and determine a plurality of key trajectory points based on the target numerical number of target straight lines. The first determining unit is further configured to obtain the second distance between the trajectory points in the trajectory group and the target straight line; sum the multiple second distances to obtain the target sum value; and determine multiple key trajectory points based on the multiple target sum values.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein when the program is run by a processor, it controls the device in which the storage medium is located to perform the method of any one of claims 1 to 4.

7. An electronic device, characterized in that, It includes one or more processors and a memory, the memory being used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method of any one of claims 1 to 4.

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