Wiring material information prediction method and device, storage medium and electronic equipment

Abstract

The invention discloses a method and a device for predicting wiring material information, a storage medium and electronic equipment. The method comprises the following steps: acquiring an initial wiring path in a power distribution extension scene and a plurality of initial track points on the initial wiring path; filtering the plurality of initial track points according to a filtering strategy to obtain at least one target track point; based on the at least one target track point, multiple key track points are determined, and in the initial wiring path, the importance degree of the key track points is higher than that of the target track points; generating a target wiring path based on the plurality of key track points, and determining a target wiring distance in the power distribution extension scene based on the target wiring path; and based on the target wiring distance and the target wiring path, predicting wiring materials in the power distribution extension scene to obtain wiring material information. According to the invention, the technical problem of low prediction accuracy of wiring material information is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of wiring material, and in particular to a method, device, storage medium and electronic device for predicting wiring material information. Background Art

[0002] When surveying an outdoor power grid for low-voltage power distribution expansion, it is necessary to evaluate and observe the site in order to estimate the direction and length of the line and, in turn, the consumables required to expand the line.

[0003] At present, the Global Positioning System (GPS system) is used to survey the site where the low-voltage power distribution expansion business is performed to obtain positioning trajectory points, and then obtain relevant information such as wiring materials. However, when the above method uses the GPS system to obtain positioning trajectory points, it will be affected by noise, resulting in deviations in the obtained positioning trajectory points, thereby causing a technical problem of low prediction accuracy of wiring material information.

[0004] With respect to the technical problem of low prediction accuracy of the above-mentioned wiring material information, no effective solution has been proposed so far. Summary of the invention

[0005] The embodiments of the present invention provide a method, device, storage medium and electronic device for predicting wiring material information, so as to at least solve the technical problem of low prediction accuracy of wiring material information.

[0006] According to one aspect of an embodiment of the invention, a method for predicting wiring material information is provided. The method includes: obtaining 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 existing in the multiple initial trajectory points; based on at least one target trajectory point, determining multiple key trajectory points, wherein in the initial wiring path, the importance of the key trajectory points is higher than the importance of the target trajectory points; based on the multiple key trajectory points, generating a target wiring path, and based on the target wiring path, determining a target wiring distance in a power distribution expansion scenario; based on the target wiring distance and the target wiring path, predicting wiring materials in a power distribution expansion scenario to obtain wiring material information.

[0007] Optionally, multiple initial trajectory points are filtered according to a filtering strategy to obtain at least one target trajectory point, including: obtaining the access status of the multiple initial trajectory points respectively; in response to the access status of the first trajectory point being an unvisited state, obtaining a first distance between the first trajectory point and the 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 except 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 target number of elements, determining the first trajectory point as a target trajectory point, and updating the access status of the first trajectory point to a visited 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, a plurality of key trajectory points are determined, including: selecting a target value trajectory points from a plurality of target trajectory points; generating a target value trajectory group based on the target value trajectory points; respectively obtaining the centroid coordinates of the target value trajectory group and the centroid points corresponding to the centroid coordinates; respectively connecting the target value centroid points with the starting point to generate a target value straight line, wherein the starting point is obtained by selecting from a plurality of initial trajectory points; and determining a plurality of key trajectory points based on the target value straight line.

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

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

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

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

[0013] According to one aspect of an embodiment of the present invention, a device for predicting wiring material information is provided, and the device also includes: a first acquisition unit, which is used to acquire an initial wiring path in a power distribution expansion scenario, and multiple initial trajectory points on the initial wiring path; a filtering unit, which is used to filter 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 a rule for filtering noise points existing in the multiple initial trajectory points; a first determination unit, which is used to determine multiple key trajectory points based on at least one target trajectory point, wherein the importance of the key trajectory points in the initial wiring path is higher than that of the target trajectory points; a second determination unit, which is used to generate a target wiring path based on the multiple key trajectory points, and determine a target wiring distance in the power distribution expansion scenario based on the target wiring path; a second acquisition unit, which is used to predict wiring materials 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 an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method in the embodiment of the present invention.

[0015] According to another aspect of an embodiment of the present invention, a processor is provided. The processor is used to run a program, wherein the method in the embodiment of the present invention is executed when the program is run.

[0016] According to another aspect of the embodiments of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in the embodiments of the present invention is implemented.

[0017] According to another aspect of an embodiment of the present invention, an electronic device is provided, the electronic device comprising a processor and a memory for storing instructions executable by the processor, wherein the processor is configured to execute the instructions to implement the method in the embodiment of the present invention.

[0018] In an embodiment of the present invention, an initial wiring path in a power distribution expansion scenario and a plurality of initial trajectory points on the initial wiring path are obtained; the plurality of 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 a rule for filtering noise points present in the plurality of initial trajectory points; based on the at least one target trajectory point, a plurality of 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 the plurality of 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. That is to say, the embodiment of the present invention can first obtain the initial wiring path in the power distribution expansion scenario, and multiple initial trajectory points on the initial wiring path, and then filter the multiple initial trajectory points according to the rule of filtering the noise points existing in the multiple initial trajectory points to obtain at least one target trajectory point, and then determine multiple key trajectory points based on the at least one target trajectory point, generate a target wiring path based on the multiple key trajectory points obtained above, and based on the target wiring path, determine the target wiring distance in the power distribution expansion scenario, and finally predict the wiring materials based on the target wiring distance and target wiring path obtained above to achieve the purpose of obtaining wiring material information. Considering that after obtaining the initial wiring path and multiple initial trajectory points on the initial wiring path, multiple initial trajectory points are filtered to obtain multiple target trajectory points, and then multiple key trajectory points can be determined from the multiple target trajectory points. The target wiring path can be generated by utilizing the multiple key trajectory points obtained above, and the target wiring distance can be further determined according to the target wiring path. Based on the target wiring distance and target wiring path obtained above, the wiring material situation required in the current distribution expansion scenario is predicted 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

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

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

[0022] Figure 3 is a flow chart of a method for acquiring key trajectory points according to an embodiment of the present invention;

[0023] Figure 4 is a flow chart of a method for generating a wiring path according to an embodiment of the present invention;

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

[0025] Figure 6 4 is a schematic diagram of a device for predicting wiring material information according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work 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 and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

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

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

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

[0031] Step S101, obtaining an initial wiring path in a power distribution expansion scenario and a plurality of initial trajectory points on the initial wiring path.

[0032] In the technical solution provided in the above step S101 of the present invention, a GPS recording instrument can be used to obtain the initial wiring path in the power distribution expansion scenario, and multiple initial track points on the initial wiring path. Among them, the multiple initial track points include the starting point and the end point of the initial wiring path, and the starting point and the end point are the points where the start and end points are pressed by the GPS handheld device, respectively.

[0033] For example, when surveying low-voltage power expansion, surveyors use GPS recording instruments to walk the wiring route to obtain several track points and determine the starting and ending points, which are the points where the GPS handheld device presses the start and end points. Among them, low-voltage power expansion is used to characterize the expansion or transformation of low-voltage distribution networks, mainly referring to the addition or update of low-voltage cables, wires, transformers and other equipment to meet the power needs of users or improve the quality of the power grid.

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

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

[0036] In the technical solution provided in the above step S102 of the present invention, after obtaining multiple initial trajectory points, the multiple initial trajectory points need to be 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 existing 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 is used to filter multiple initial trajectory points to obtain at least one target trajectory point, thereby filtering out all points that meet the clustering conditions, and finally the remaining points that are not clustered are noise points. Compared with the typical clustering algorithm (e.g., the DBSCAN algorithm), it is not necessary to divide the coordinate information points into multiple clusters, but only needs to classify all the coordinate information points within a certain range in the actual trajectory into one cluster.

[0038] It should be noted that this is only a preferred implementation method 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 multiple initial trajectory points are filtered according to the filtering strategy, the method and process for obtaining at least one target trajectory point are within the protection scope of the present invention and are not listed here.

[0039] Step S103: determining a plurality of key trajectory points based on at least one target trajectory point.

[0040] In the technical solution provided in the above 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, wherein, in the initial wiring path, the importance of the key trajectory points is higher than the importance of the target trajectory points.

[0041] Optionally, after the track point noise filtering module obtains the track point samples from which the noise has been filtered, key track points that can represent the routing path can be found from the track point samples from which the noise has been filtered.

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

[0043] For example, after obtaining N trajectory points and each trajectory point corresponds to a geographic location coordinate, a parameter K can be set, and the geographic location coordinates of the key trajectory points can be obtained from the first K coordinates of the geographic location coordinates of multiple trajectory points to determine multiple key trajectory points.

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

[0045] Step S104, generating a target wiring path based on a plurality of key trajectory points, and determining a target wiring distance in a power distribution expansion scenario based on the target wiring path.

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

[0047] Optionally, by using a wiring path formulation module, the obtained multiple key trajectory points are connected to obtain a target wiring path, and the target wiring path is measured to obtain a target wiring distance in the power distribution expansion scenario. The target wiring path may be a final wiring path. The target wiring distance may be a final total wiring distance.

[0048] For example, in the wiring path key coordinate acquisition module, the key trajectory points among the first K trajectory points can be obtained. In the wiring path formulation module, the first K trajectory points are removed from the original trajectory point set, and then the key trajectory points are used as new starting points. The wiring path key coordinate acquisition module is re-adopted to obtain key trajectory points one by one in turn, and the trajectory starting point of the original trajectory point is connected to the key trajectory points generated before and after in time until they are connected to the end point. Finally, the distance of each line segment is added to obtain the total distance of the wiring line.

[0049] It should be noted that this is only a preferred implementation method for determining the target wiring distance in the power distribution expansion scenario, and the process and method for determining the target wiring distance in the 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 the power distribution expansion scenario is based on the target wiring path, they are within the scope of protection of the present invention and will not be listed here.

[0050] Step S105 , 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 usage information.

[0051] In the technical solution provided in the above step S105 of the present invention, according to the obtained target wiring distance and target wiring path, the wiring material estimation module can be used to predict the wiring material in the power distribution expansion scenario to obtain the wiring material information.

[0052] Optionally, the wiring material information may include tower material information, insulator material information, and line material information. Among them, the tower material information is used to characterize the material conditions of the tower, and can be called the total tower material. The insulator material information is used to characterize the installation position and installation quantity of the insulator, and can be called the total insulator material. The line material information can be called the total line material.

[0053] For example, after obtaining the target wiring distance and target wiring path using the wiring path formulation module, the wiring material estimation module can be used to calculate the wiring material information required for low-voltage business expansion and its total wiring distance. The wiring material information includes the total line material, the total tower material, and the total insulator material.

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

[0055] In the above steps S101 to S105 of the present invention, an initial wiring path in a power distribution expansion scenario and a plurality of initial trajectory points on the initial wiring path can be first obtained, and then the plurality of initial trajectory points can be filtered according to a rule for filtering noise points existing in the plurality of initial trajectory points to obtain at least one target trajectory point, and then a plurality of key trajectory points can be determined based on the at least one target trajectory point, and a target wiring path can be generated based on the plurality of key trajectory points obtained above, and based on the target wiring path, a target wiring distance in a power distribution expansion scenario can be determined, and finally, based on the target wiring distance and the target wiring path obtained above, the wiring materials can be predicted to achieve the purpose of obtaining wiring material information. Considering that after obtaining the initial wiring path and multiple initial trajectory points on the initial wiring path, multiple initial trajectory points are filtered to obtain multiple target trajectory points, and then multiple key trajectory points can be determined from the multiple target trajectory points. The target wiring path can be generated by utilizing the multiple key trajectory points obtained above, and the target wiring distance can be further determined according to the target wiring path. Based on the target wiring distance and target wiring path obtained above, the wiring material situation required in the current distribution expansion scenario is predicted 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.

[0056] The above method of this embodiment is further introduced below.

[0057] As an optional implementation method, multiple initial trajectory points are filtered according to a filtering strategy to obtain at least one target trajectory point, including: obtaining the access status of multiple initial trajectory points respectively; in response to the access status of the first trajectory point being an unvisited state, obtaining a first distance between the first trajectory point and the 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 except 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 target number of elements, determining the first trajectory point as a target trajectory point, and updating the access status of the first trajectory point to a visited 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 take the multiple initial trajectory points as a sample set, and the access status of the multiple initial trajectory points is obtained respectively. If any trajectory point is selected from the multiple initial trajectory points at this time, that is, the first trajectory point, and the access status of the first trajectory point is the unvisited state, then the first distance between the first trajectory point and the second trajectory point selected from the multiple trajectory points other than the first trajectory point can be obtained, and the first distance is compared with the first distance threshold. If the first distance is less than the first distance threshold, the neighborhood set of the first trajectory point can be determined. If the number of elements in the neighborhood set is greater than or equal to the target number of elements at this time, the first trajectory point can be determined as the target trajectory point, and the access status of the first trajectory point is updated to the visited state. The above process is repeated, and when the access status of all initial trajectory points is the visited state, the loop can be stopped, which means that each point in the multiple initial trajectory points has been filtered, so that multiple target trajectory points can be determined.

[0059] Optionally, when the first trajectory point passes through p a The second trajectory point is represented by p b When expressing the first distance, it can be expressed by d a，b The first distance threshold may be a preset value and may be represented by a parameter ε. x When representing, the neighborhood set can be represented by the ε-neighborhood subsample set N ε (p x ). The target element number may be a preset value and is represented by minPts. The target trajectory point may be referred to as a core point.

[0060] For example, the process of using the track point noise filtering module to determine multiple target track points can be as follows: all track points are taken as a sample set, and then the access status of all samples is marked as unvisited, and each sample is traversed. At the beginning 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 is started; if the sample has not been visited, the access status of the sample is marked as unvisited. Then it is determined whether the current sample is a core point. In this embodiment, d a，b Indicates p a to p b The Euclidean distance is as shown in the following formula:

[0061]

[0062] In the above formula, p a It is used to represent any point in the sample set, and the coordinates of the point are (x a ,y a ). b Used to represent the sample set except p a Any point outside the b ,y b ). At this time, the distance d is obtained a，b After that, if the distance satisfies the following formula, it is considered that p a In p b In the neighborhood of b Also in p a In the neighborhood of:

[0063] d a，b <ε

[0064] In the above formula, the parameter ε is used to characterize the distance threshold between samples, and then according to the above formula, p can be found x The ε-neighborhood subsample set N ε (p x ), then the judgment condition of 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 sample number threshold in the neighborhood of each sample. If the trajectory point p x The ε-neighborhood subsample set satisfies the above formula, then it is considered that p x It is the core point. It should be noted that ε and minPts are important adjustment parameters in this module, which directly affect the effect and strength of noise filtering.

[0067] Further, according to the above process, it is possible to continue to determine whether the current sample is a core point. If it is not a core point, the traversal of the next sample is started. If it is a core point, the point is added to the target cluster (cluster C), and the collection of all samples in the neighborhood of the sample is obtained. The sample collection can be represented by N. Traverse each sample in N again, mark the traversed samples as visited, and add the sample to cluster C. If a sample is found to be a core point during this traversal process, all samples in the neighborhood of the sample are added to the set N. This process continues until all samples in the set N have been visited, and 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 finally obtained. Among them, the core points obtained by filtering all samples and the coordinates of the core points constitute the noise-filtered trajectory geographic coordinate information, which are input into the wiring path key coordinate acquisition module for processing.

[0068] As an optional implementation method, based on at least one target trajectory point, multiple key trajectory points are determined, including: selecting a target value trajectory point from multiple target trajectory points; generating a target value trajectory group based on the target value trajectory point; respectively obtaining the centroid coordinates of the target value trajectory group and the centroid point corresponding to the centroid coordinates; respectively connecting the target value centroid points with the starting point to generate a target value straight line, wherein the starting point is obtained by selecting from multiple initial trajectory points; and determining multiple key trajectory points based on the target value straight line.

[0069] In this embodiment, the wiring path key coordinate acquisition module is used to select a target value trajectory point from multiple target trajectory points, and then generate a target value trajectory group based on the target value trajectory point, and then obtain the centroid coordinates of the target value trajectory group and the centroid point corresponding to the centroid coordinate, and further connect the target value centroid points with the starting point to generate a target value line, and finally, according to the target value line obtained above, the purpose of determining multiple key trajectory points can be achieved.

[0070] Optionally, the target value may be a preset value and may be represented by a parameter K. Then, K trajectory points may be selected from a plurality of target trajectory points. The K trajectory points may be represented by (P1, P2, ..., P k ) is represented; according to K trajectory points, K trajectory groups are generated, and the K groups can be represented by (P1), (P1, P2), (P1, P2, P3), …, (P1, P2, …, P k ) to represent; and then obtain the center of gravity coordinates of the K trajectory groups respectively, and the K center of gravity coordinates can be obtained by Q1, Q2, Q3, ..., Q kAfter representing the center of gravity point corresponding to the center of gravity coordinates, connect the K center of gravity points with the starting point to generate K target straight lines. Then the K target straight lines can 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, and K trajectory groups are generated according to the first K points in the trajectory point sample set that has been filtered out of noise obtained by the trajectory point noise filtering module, namely (P1), (P1, P2), (P1, P2, P3), ..., (P1, P2, ..., P k ). Then calculate the barycentric coordinates of these K groups of points respectively, and get K barycentric coordinates: Q1, Q2, Q3, ..., Q k Among them, the calculation point set (P1, P2…P i )’s center of gravity Q i The coordinates are shown in the following formula:

[0072]

[0073] In the above formula, i is used to represent the number of trajectory points in the point set, x gi Used to represent the center of gravity coordinate Q i The x-coordinate, y- gi Used to represent the center of gravity coordinate Q i Then connect the starting point of the trajectory with the K centroid coordinates to obtain K straight lines, namely l1, l2…l k . Assume that the i-th line l i The equation for is as follows:

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

[0075] In the above formula, A i , B i , C i are used to represent the coefficients of the i-th straight line, and the 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, based on the target numerical value item target straight line, multiple key trajectory points are determined, including: respectively obtaining the second distances between the trajectory points in the trajectory group and the target straight 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.

[0079] In this embodiment, the wiring path key coordinate acquisition module is used to obtain the second distances between the trajectory points in the trajectory group and the target straight line according to the obtained target numerical value item target straight line, and then the multiple second distances are summed 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 based on the minimum sum value, multiple key trajectory points are determined.

[0080] Optionally, any trajectory point is selected from the trajectory group, and the trajectory point can be obtained by P i To represent, the target straight line can be expressed by l j If we express it as i The target straight line j The second distance between i，j The target and value corresponding to the jth target line can be expressed by D j To express.

[0081] For example, after obtaining K straight lines using the wiring path key coordinate acquisition module, the sum of the distances from the P tracks contained in the P point set to each straight line is calculated. j The sum of the distances can be calculated using the following formula:

[0082]

[0083] Among them, d i，j Used to represent the trajectory point P i With straight line l j The distance between the i-th trajectory point P i To the jth straight line l j The distance can be calculated by the following formula:

[0084]

[0085] Then, find the minimum value of the sum of the distances from the trajectory point to the straight line. The calculation formula is as shown in the following formula:

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

[0087] From the above formula, we can find the barycentric coordinates corresponding to the minimum value of the sum of distances. Assuming that the barycentric coordinates are Qi , then Q i A point determined on the wiring path is a key trajectory point. According to the above process, the purpose of determining multiple key trajectory points can be achieved, and the multiple key trajectory points are input into the wiring path formulation module for the next step of processing.

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

[0089] In this embodiment, the wiring path formulation module can be used to obtain the timestamps of multiple key trajectory points respectively, and then sort the multiple key trajectory points according to the multiple timestamps obtained above to obtain the sorted multiple key trajectory points, and further 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, and then the sorted multiple key trajectory points can be connected in sequence to obtain a target wiring path. According to the target wiring path, the purpose of determining the target wiring distance can be achieved.

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

[0092] In this embodiment, the wiring path formulation module is used to connect the sorted multiple key trajectory points to obtain the target wiring path. According to the target wiring path obtained above, multiple third distances are determined, and then the multiple third distances are summed to obtain the target wiring distance. The third distance can be the distance between any adjacent key trajectory points, and can be obtained by S i，i+1 The target wiring distance can be expressed by D 总 To express.

[0093] For example, using the wiring path formulation module, the process of obtaining the target wiring distance is as follows. First, use the wiring path key coordinate acquisition module to find all key trajectory points, put them in a set E, and then sort them according to the timestamp, and use the last remaining number of trajectory points less than K as the condition for judging whether it is the last key trajectory point. Then connect the starting point and the first key trajectory point obtained, and then connect all the key trajectory points in sequence according to the timestamp until they are connected to the end point to determine the total wiring distance. Among them, the distance between the key trajectory points can be expressed by the following formula:

[0094]

[0095] In the above formula, S i，i+1 It is used to represent the distance between the i+1th key trajectory point and the ith key trajectory point. Then the distance of each line segment is calculated in turn, and all distances are added together to get the total wiring distance. The calculation formula for the total wiring distance is as follows:

[0096]

[0097] In the above formula, M is used to represent the total number of paths on the outdoor wiring path, and D 总 It is used to represent the total wiring distance. Finally, the total wiring distance and the key trajectory point set 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 materials are predicted in the distribution expansion scenario to obtain the wiring material information, including: based on the target wiring path, determining the pole tower material information in the wiring material information; based on the pole tower material information, determining the insulator material information in the wiring material information; based on the target wiring distance, determining the line material information in the wiring material information.

[0099] In this embodiment, the wiring material estimation module is used to determine the pole tower material information in the wiring material information according to the obtained target wiring path, and then the insulator material information can be determined according to the above-obtained pole tower material information. According to 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 a target product, and the line material information is determined based on the target product.

[0101] For example, using the wiring material estimation module, the process of obtaining wiring material information according to the target wiring distance and target wiring path is as follows. First, a pole tower is arranged for all samples in the obtained sample set E, and a pole tower is arranged at a certain distance inside the branch line segment, and finally the total number of pole towers required in the distribution expansion scenario is determined, which can be expressed by the following formula:

[0102]

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

[0104] q=λh

[0105] In the above formula, q is used to represent the total number of insulators, and λ is used to represent the number of insulators required on each tower. Finally, according to the total line distance D total output by the wiring path formulation module, the total amount of line materials can be determined, as shown in the following formula:

[0106] u=D 总 ×4×u(1<u<1.1)

[0107] Among them, u is used to characterize the total amount of line materials, and μ is used to represent the inclination influence coefficient of line materials. Since the line itself has a certain weight, under the influence of gravity, the line usually bends to a certain extent. Therefore, consider multiplying the total length by a tilt influence coefficient. At the same time, consider the use of a three-phase four-wire system, and each tower is connected by four lines to calculate the total amount of line materials.

[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 first obtained, and then the multiple initial trajectory points can be filtered according to the rule of filtering the noise points existing in the multiple initial trajectory points to obtain at least one target trajectory point, and then based on the at least one target trajectory point, multiple key trajectory points can be determined, and based on the multiple key trajectory points obtained above, a target wiring path is generated, and based on the target wiring path, the target wiring distance in the power distribution expansion scenario can be determined, and 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. Considering that after obtaining the initial wiring path and multiple initial trajectory points on the initial wiring path, multiple initial trajectory points are filtered to obtain multiple target trajectory points, and then multiple key trajectory points can be determined from the multiple target trajectory points. The target wiring path can be generated by utilizing the multiple key trajectory points obtained above, and the target wiring distance can be further determined according to the target wiring path. Based on the target wiring distance and target wiring path obtained above, the wiring material situation required in the current distribution expansion scenario is predicted 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.

[0109] The technical solution of the embodiment of the present invention is illustrated below in conjunction with preferred implementation modes.

[0110] When the power company conducts low-voltage business expansion survey, the traditional outdoor field survey of low-voltage business expansion relies on manual observation and manual recording, that is, through on-site evaluation and observation, the direction and length of the line are estimated, and the consumables of the business expansion line are further estimated. This simple use of manual labor to complete the business expansion survey brings problems such as untimely survey data update and unreasonable resource allocation to the power grid. In view of the above problems, it is necessary to develop a digital method for outdoor field survey of low-voltage business expansion in the process of digitalization of the power industry. The digital development of outdoor field survey is often achieved by GPS system. Specifically, the staff uses handheld GPS positioning equipment to survey the site of low-voltage distribution expansion business, obtain positioning trajectory points, and then obtain relevant information such as wiring materials. However, when the above method uses the GPS system to obtain positioning trajectory points, it will be affected by noise, resulting in deviations in the obtained positioning trajectory points, and thus there is a technical problem of low prediction accuracy of wiring material information.

[0111] Therefore, in order to solve the above problems, the present invention proposes a low-voltage business expansion outdoor wiring survey method based on the GPS system. The method first uses the GPS positioning device to collect the required trajectory points on the wiring path, and determines the starting point and the end point at the same time, and then uses the DBSCAN-based trajectory noise filtering module to filter the GPS trajectory points for noise. Subsequently, after obtaining the filtered trajectory points, the first step is to set a point set of K groups of trajectory points based on the first K trajectory points, and the second step is to calculate the centroid coordinates Q of the K groups of point sets on this basis. The third step is to connect the starting point with all the centroids Q to obtain K groups of straight lines, and then calculate the distances from the first K trajectory points to each straight line respectively, and compare to obtain the shortest distance. The centroid of the straight line corresponding to this distance is used as a point determined on the line, and this point is connected to the starting point, and this point is used as a new starting point. After removing the first K trajectory points from the point set, the content of the third step is repeated again until it is connected to the final end point to obtain the final wiring path. According to 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 the low-voltage business expansion survey, the surveyor can use the GPS recording instrument to walk the wiring route, obtain the GPS track points on the wiring path, and then use the track point noise filtering module to filter the noise of the obtained track points. Next, use the wiring path key coordinate acquisition module to obtain the key track points of the track points that have been filtered out of noise, and then use the wiring path formulation module to connect the starting point and the key track points obtained in sequence until they are connected to the end point, so as to obtain the optimized wiring path. Finally, the wiring material estimation module is used to estimate the materials required for wiring.

[0113] Figure 2 is a flow chart of a method for obtaining filtered trajectory points according to an embodiment of the present invention. Figure 2 As shown, the method can be implemented in the trajectory point noise filtering module to obtain the filtered trajectory points. The above-mentioned method for obtaining the filtered trajectory points mainly includes the following steps:

[0114] Step S201, collecting track points through a GPS device.

[0115] In this embodiment, in the track point noise filtering module, track points are collected by GPS equipment. In the track point noise filtering module, the improved DBSCAN clustering algorithm is used to filter multiple initial track points to obtain at least one target track point, so that all points that meet the clustering conditions are screened out, and the remaining points that are not clustered are noise points. Compared with the typical DBSCAN algorithm, it is not necessary to divide the coordinate information points into multiple clusters, but only to classify all the coordinate information points within a certain range in the actual track into one cluster.

[0116] Optionally, during the low voltage expansion survey, the surveyor can use a GPS recording instrument to walk the wiring route to obtain several track points and determine the starting point and the end point. Assuming there are N track points in total, the obtained set of data can be sorted in chronological order, that is: (P1, P2, .., P N ), where P1 is used to represent the starting point of the trajectory point, P N It is used to indicate the end point of the trajectory point. Each trajectory point corresponds to a geographical location coordinate, that is, the geographical location coordinate of the i-th point can be expressed as P i =(x i ,y i ).

[0117] Step S202, selecting unvisited track points.

[0118] Step S203, determining whether the input trajectory point is a core point.

[0119] In this embodiment, it can be determined whether the trajectory point input at this time is a core point. If it is, step S204 is executed; if not, step S207 is executed.

[0120] In this embodiment, all trajectory points are taken as a sample set, and then the access status of all samples is marked as unvisited, and each sample is traversed. At the beginning 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, the access status of the sample is marked as unvisited. Then it is determined whether the current sample is a core point. In this embodiment, d a，b Indicates p a to p b The Euclidean distance is as shown in the following formula:

[0121]

[0122] In the above formula, p a It is used to represent any point in the sample set, and the coordinates of the point are (x a ,y a ).b Used to represent the sample set except p a Any point outside the b ,y b ). At this time, the distance d is obtained a，b After that, if the distance satisfies the following formula, it is considered that p a In p b In the neighborhood of b Also in p a In the neighborhood of:

[0123] d a，b <ε

[0124] Among them, the parameter ε is used to characterize the distance threshold between samples, and then according to the above formula, p can be found x The ε-neighborhood subsample set N ε (p x ), then the judgment condition of 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 sample number threshold in the neighborhood of each sample. If the trajectory point p x The ε-neighborhood subsample set satisfies the above formula, then it is considered that p x It is the core point. It should be noted that ε and minPts are important adjustment parameters in this module, which directly affect the effect and strength 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, retaining the core points.

[0129] Step S205, determining whether there are any unprocessed points.

[0130] In this embodiment, it is necessary to determine whether there are unprocessed points. If yes, step S207 is executed; if no, step S206 is executed.

[0131] Step S206, filtered trajectory points.

[0132] Step S207: mark as a noise point.

[0133] In this embodiment, according to the above process, it is possible to continue to determine whether the current sample is a core point. If it is not a core point, the traversal of the next sample is started. If it is a core point, the point is added to cluster C, and the collection of all samples in the neighborhood of the sample is obtained. The sample collection can be represented by N. Traverse each sample in N again, mark the traversed samples as visited, and add the sample to cluster C. If a sample is found to be a core point during this traversal process, all samples in the neighborhood of the sample are added to the set N. This process continues until all samples in the set N have been visited, and 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 finally obtained. Among them, the core points obtained by filtering all samples and the coordinates of the core points constitute the noise-filtered trajectory geographic coordinate information, which are input into the wiring path key coordinate acquisition module for processing.

[0134] Figure 3 is a flow chart of a method for obtaining key trajectory points according to an embodiment of the present invention. Figure 2 After obtaining the filtered trajectory points in the trajectory point noise filtering module, the filtered trajectory points are input into the wiring path key coordinate acquisition module to obtain the key trajectory points, that is, Figure 3 As shown, it mainly includes the following steps:

[0135] Step S301, determining the starting point and the end point of the trajectory.

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

[0137] In this embodiment, a parameter K is set, and K trajectory groups are generated according to the first K points in the trajectory point sample set from which the noise has been filtered out, that is, (P1), (P1, P2), (P1, P2, P3), .., (P1, P2, ..., P k ).

[0138] Step S303, determining the centroid coordinates of the K groups of trajectory groups respectively.

[0139] In this embodiment, according to K groups of trajectory groups, the center of gravity coordinates of the K groups of point sets are respectively calculated to obtain K center of gravity coordinates: Q1, Q2, Q3, ..., Q k Among them, the calculation point set (P1, P2…P i )’s center of gravity Q i The coordinates are shown in the following formula:

[0140]

[0141] In the above formula, i is used to represent the number of trajectory points in the point set, xgi Used to represent the center of gravity coordinate Q i The x-coordinate, y- gi Used to represent the center of gravity coordinate Q i The y coordinate of

[0142] Step S304, connecting the starting point and K centroid coordinates into K straight lines.

[0143] In this embodiment, the starting point of the trajectory is connected with K centroid coordinates to obtain K straight lines, namely l1, l2…l k . Assume that the i-th line l i The equation for is as follows:

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

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

[0146]

[0147] According to the above process, K target straight lines can be obtained.

[0148] Step S305, respectively calculating the distances from the K trajectory points to all straight lines.

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

[0150]

[0151] Among them, d i，j Used to represent the trajectory point P i With straight line l j The distance between the i-th trajectory point P i To the jth straight line l j The distance can be calculated by the following formula:

[0152]

[0153] Then, find the minimum value of the sum of the distances from the trajectory point to the straight line. The calculation formula is as shown in the following formula:

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

[0155] From the above formula, we can know that the centroid coordinates corresponding to the minimum value of the sum of distances can be found.

[0156] Step S306, determining a plurality of key trajectory points.

[0157] In this embodiment, according to the minimum value of the sum of the distances from the trajectory point to the straight line, the center of gravity coordinate corresponding to the minimum value of the sum of the distances can be found. Assume that the center of gravity coordinate is Q i , then Q i A point determined on the wiring path is a key trajectory point. According to the above process, the purpose of determining multiple key trajectory points can be achieved, and the multiple key trajectory points are input into the wiring path formulation module for the next step of processing.

[0158] Figure 4 1 is a flow chart of a method for generating a wiring path according to an embodiment of the present invention. Figure 3 After determining a plurality of key trajectory points in the wiring path key coordinate acquisition module, the plurality of key trajectory points are input into the wiring path formulation module to generate a wiring path, that is, Figure 4 As shown, it mainly includes the following steps:

[0159] Step S401, selecting a starting point from the obtained multiple key trajectory points.

[0160] Step S402, connecting the starting point and a plurality of key track points in sequence until the end point is reached, thereby generating a wiring path.

[0161] Step S403, calculating the total wiring distance based on the wiring path.

[0162] In this embodiment, the wiring path key coordinate acquisition module is first used to obtain all key trajectory points, which are placed in a set E, and then sorted according to the timestamp. The number of remaining trajectory points is less than K as the condition for determining whether it is the last key trajectory point. Then, the starting point and the first obtained key trajectory point are connected, and then all key trajectory points are connected in sequence according to the timestamp until they are connected to the end point, so as to determine the total wiring distance. Among them, the distance between key trajectory points can be expressed by the following formula:

[0163]

[0164] In the above formula, s i，i+1It is used to represent the distance between the i+1th key trajectory point and the ith key trajectory point. Then the distance of each line segment is calculated in turn, and all distances are added together to get the total wiring distance. The calculation formula for the total wiring distance is as follows:

[0165]

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

[0167] In this embodiment, in the wiring path key coordinate acquisition module, the key trajectory points among the first K trajectory points can be obtained. In the wiring path formulation module, the first K trajectory points are removed from the original trajectory point set, and then the key trajectory points are used as new starting points. The wiring path key coordinate acquisition module is re-adopted to obtain key trajectory points one by one in turn, and the trajectory starting point of the original trajectory point is connected to the key trajectory points generated before and after in time until they are connected to the end point. Finally, the distance of each line segment is added to obtain the total distance of the wiring line.

[0168] Figure 5 is a flow chart of a method for estimating wiring material information according to an embodiment of the present invention. Figure 4 After the wiring path is generated in the wiring path formulation module, the wiring path is input into the wiring material estimation module to estimate the wiring material information, that is, Figure 5 As shown, it mainly includes the following steps:

[0169] Step S501, estimating the total amount of line material used.

[0170] In this embodiment, a pole tower is arranged for all samples in the obtained sample set E, and a pole tower is arranged at a certain interval inside the branch line segment, and the total number of pole towers required in the power distribution expansion scenario is finally determined, which can be expressed by the following formula:

[0171]

[0172] In the above formula, h is used to represent the total number of towers required, α is used to represent the spacing of the tower distribution, and the ceil() function is used to indicate that the value is rounded up.

[0173] Step S502, estimating the total amount of materials required for the tower.

[0174] In this embodiment, after the number of pole towers is obtained, a fixed number of insulators need to be installed on each pole tower, and then the total number of insulators required to be installed in the power distribution expansion scenario can be obtained, which can be expressed by the following formula:

[0175] q=λh

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

[0177] Step S503, estimating the total amount of insulator material used.

[0178] In this embodiment, according to the total line distance D total output by the wiring path formulation module, the total line material consumption can be determined, that is, as shown in the following formula:

[0179] u=D 总 ×4×u(1<u<1.1)

[0180] Among them, u is used to characterize the total amount of line materials, and μ is used to represent the inclination influence coefficient of line materials. Since the line itself has a certain weight, under the influence of gravity, the line usually bends to a certain extent. Therefore, consider multiplying the total length by a tilt influence coefficient. At the same time, consider the use of a three-phase four-wire system, and each tower is connected by four lines to calculate the total amount of line materials.

[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 first obtained, and then the multiple initial trajectory points can be filtered according to the rule of filtering the noise points existing in the multiple initial trajectory points to obtain at least one target trajectory point, and then based on the at least one target trajectory point, multiple key trajectory points can be determined, and based on the multiple key trajectory points obtained above, a target wiring path is generated, and based on the target wiring path, the target wiring distance in the power distribution expansion scenario can be determined, and 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. Considering that after obtaining the initial wiring path and multiple initial trajectory points on the initial wiring path, multiple initial trajectory points are filtered to obtain multiple target trajectory points, and then multiple key trajectory points can be determined from the multiple target trajectory points. The target wiring path can be generated by utilizing the multiple key trajectory points obtained above, and the target wiring distance can be further determined according to the target wiring path. Based on the target wiring distance and target wiring path obtained above, the wiring material situation required in the current distribution expansion scenario is predicted 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.

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

[0183] Figure 6 is a schematic diagram of a device for predicting wiring material information according to an embodiment of the present invention. Figure 6 As shown, a prediction device 600 for 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 an initial wiring path in a power distribution expansion scenario and a plurality of initial trajectory points on the initial wiring path.

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

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

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

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

[0189] Optionally, the filtering unit 602 may include: a first acquisition module, used to respectively acquire the access status of multiple initial trajectory points; a second acquisition module, used to obtain a first distance between the first trajectory point and the second trajectory point in response to the access status of the first trajectory point being an unvisited state, 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 except the first trajectory point; a first determination module, used 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, used to determine the first trajectory point as a target trajectory point in response to the number of elements in the neighborhood set being greater than or equal to the target number of elements, and update the access status of the first trajectory point to a visited state; a third determination module, used to determine multiple target trajectory points based on the updated access status of the multiple initial trajectory points.

[0190] Optionally, the first determination unit 603 may include: a selection module, used to select a target value trajectory point from multiple target trajectory points; a first generation module, used to generate a target value trajectory group based on the target value trajectory point; a third acquisition module, used to respectively obtain the centroid coordinates of the target value trajectory group and the centroid point corresponding to the centroid coordinates; a second generation module, used to respectively connect the target value centroid points with the starting point to generate a target value line, wherein the starting point is obtained by selecting from multiple initial trajectory points; and a fourth determination module, used to determine multiple key trajectory points based on the target value line.

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

[0192] Optionally, the second determination unit 604 may include: a fourth acquisition module, used to respectively obtain the timestamps of multiple key trajectory points; a sorting module, used to sort the multiple key trajectory points based on the multiple timestamps to obtain the sorted multiple key trajectory points; 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 sub-module, used to connect the sorted multiple key trajectory points to obtain a target wiring path; a second determination sub-module, used to determine multiple third distances based on the target wiring path; and a fourth acquisition sub-module, used to sum the multiple third distances to obtain the target wiring distance.

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

[0195] In this embodiment, an initial wiring path in a power distribution expansion scenario and a plurality of initial trajectory points on the initial wiring path are acquired by a first acquisition unit; a plurality of initial trajectory points are filtered by a filtering unit according to a filtering strategy to obtain at least one target trajectory point, wherein the filtering strategy is used to characterize a rule for filtering noise points existing in the plurality of initial trajectory points; a plurality of key trajectory points are determined by a first determination unit based on at least one target trajectory point, wherein in the initial wiring path, the importance of the key trajectory points is higher than that of the target trajectory points; a target wiring path is generated by a second determination unit based on the plurality of key trajectory points, and a target wiring distance in a power distribution expansion scenario is determined based on the target wiring path; a wiring material is predicted by a second acquisition unit based on the target wiring distance and the target wiring path in a power distribution expansion scenario 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, which includes a stored program, wherein when the program is executed by a processor, the device where the readable storage medium is located is controlled to execute the method for predicting wiring material information in the embodiment.

[0197] According to an embodiment of the present invention, a processor is further provided. The processor is used to run a program. When the program is run, the method for predicting wiring material information in the embodiment is executed.

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

[0199] According to an embodiment of the present invention, an electronic device is also provided, the electronic device comprising a processor and a memory for storing instructions executable by the processor, wherein the processor is configured to execute the instructions to implement the method for predicting wiring material information in the embodiment of the present invention.

[0200] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0201] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0202] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic, for example, the division of units can be a logical function division, and there can be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

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

[0204] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0205] If the integrated unit is implemented in the form of 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, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0206] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for predicting wiring material information, characterized in that: include: Acquire an initial wiring path in a power distribution expansion scenario, and a plurality of initial trajectory points on the initial wiring path; Filtering 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 a rule for filtering noise points existing in the plurality of initial trajectory points; Based on at least one of the target trajectory points, determining a plurality of key trajectory points, wherein in the initial routing path, the importance of the key trajectory points is higher than the importance of the target trajectory points; Based on the plurality of 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 material usage is predicted in the power distribution expansion scenario to obtain wiring material usage information.

2. The method according to claim 1, characterized in that Filtering the plurality of initial trajectory points according to the filtering strategy to obtain at least one target trajectory point includes: Respectively obtaining access statuses of a plurality of the initial trajectory points; In response to the access state of the first track point being an unvisited state, obtaining a first distance between the first track point and a second track point, wherein the first track point is any point among the plurality of initial track points, and the second track point is any point among the plurality of initial track points except the first track 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 target number of elements, determining the first trajectory point as a target trajectory point, and updating the access state of the first trajectory point to a visited state; Based on the updated access status of the plurality of initial track points, a plurality of target track points are determined.

3. The method according to claim 1, characterized in that Based on at least one of the target trajectory points, a plurality of key trajectory points are determined, including: Selecting a target value of trajectory points from the plurality of target trajectory points; Based on the target value number of trajectory points, generating the target value number of trajectory groups; Respectively obtain the centroid coordinates of each target value trajectory group and the centroid point corresponding to the centroid coordinates; Connecting the target value centroid points with the starting point respectively to generate the target value straight line, wherein the starting point is selected from the multiple initial trajectory points; Based on the target value item and the target straight line, a plurality of the key trajectory points are determined.

4. The method according to claim 3, characterized in that Based on the target value item target straight line, a plurality of the key trajectory points are determined, including: respectively obtaining second distances between the trajectory points in the trajectory group and the target straight line; performing a sum operation on a plurality of the second distances to obtain a target sum value; Based on the multiple targets and values, multiple key trajectory points are determined.

5. The method according to claim 1, characterized in that Based on the plurality of 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, including: Respectively obtain timestamps of a plurality of key trajectory points; Based on the multiple timestamps, sorting the multiple key trajectory points to obtain the sorted multiple key trajectory points; Based on the sorted plurality of key trajectory points, the target wiring distance and the target wiring path are obtained.

6. The method according to claim 5, characterized in that Based on the sorted plurality of key trajectory points, the target wiring distance and the target wiring path are obtained, including: Connecting the sorted plurality of key trajectory points to obtain the target wiring path; Based on the target routing path, determining a plurality of third distances; A sum operation is performed on a plurality of the third distances to obtain the target wiring distance.

7. The method according to claim 1, characterized in that Based on the target wiring distance and the target wiring path, the wiring material is predicted in the power distribution expansion scenario to obtain wiring material information, including: Based on the target wiring path, determining the 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, line material information in the wiring material information is determined.

8. A device for predicting wiring material information, characterized in that: include: 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 a rule for filtering noise points existing in the plurality of initial trajectory points; A first determining unit is used to determine a plurality of key trajectory points based on at least one of the target trajectory points, wherein, in the initial routing path, the importance of the key trajectory points is higher than the importance of the target trajectory points; A second determining 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; The second acquisition unit is used to predict the wiring material usage in the power distribution expansion scenario based on the target wiring distance and the target wiring path to obtain wiring material usage information.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: The invention comprises one or more processors and a memory, wherein the memory is 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 implement the method described in any one of claims 1 to 7.

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