A smart optimization allocation system for power pole installation resources

Abstract

This invention discloses an intelligent optimization and allocation system for power pole tower installation resources. This invention relates to the field of power pole tower technology and solves the problem of mismatch between the total installation volume and actual demand caused by the failure to quantitatively calculate based on the three-dimensional structural characteristics of power pole towers and the spatial distribution of mounting points. This invention effectively reduces the intersection range between installations by employing a dynamic adjustment mechanism of "adjacent undetermined point identification + connection direction extension + process feature verification" for installation nodes that intersect in the optimal process. While ensuring comprehensive coverage, it allows each installation node to fully play its role, improving the utilization rate of mounting point resources. Simultaneously, the optimized installation node layout better meets cable safety spacing requirements, reducing safety hazards caused by dense intersections and aligning with the quality control requirements of cross-industry safety standards and data governance systems.

Description

Technical Field

[0001] This invention relates to the field of power pole technology, specifically to an intelligent optimization and allocation system for power pole installation resources. Background Technology

[0002] Against the backdrop of deep collaboration between the energy and communications industries and the accelerated promotion of the "one tower, multiple uses" sharing model, the optimized allocation of power pole installation resources has become a key link in improving infrastructure utilization and supporting the construction of digital grids and smart cities.

[0003] However, the current allocation of communication installation resources on power poles still faces many technical bottlenecks. Existing solutions are unable to meet the requirements for precise, efficient, and intelligent configuration: the total amount of communication installations lacks scientific quantitative basis, and traditional configuration methods rely heavily on manual experience to estimate the number of installations, which can easily lead to problems of "insufficient coverage" or "over-installation"—either too few installations result in incomplete coverage of the pole mounting area, affecting communication transmission, power capacity expansion, and other service needs; or too many installations lead to a waste of mounting point resources, or even exceed the pole's load-bearing limit, causing safety hazards.

[0004] Meanwhile, existing technologies fail to quantitatively calculate based on the three-dimensional structural characteristics of power poles and the spatial distribution of mounting points, resulting in a mismatch between the total amount of installations and actual needs, as well as the pole's load-bearing capacity. Furthermore, the screening of installation progress and the layout of nodes lack intelligent optimization mechanisms. Traditional installation scheme planning relies on manual screening, which is not only inefficient but also fails to meet the core requirements of "comprehensive coverage" and "reduced overlap," often leading to redundant installation areas and low resource utilization efficiency. For established installation schemes, there is a lack of dynamic adjustment methods, making it impossible to specifically address issues such as insufficient safety clearance and signal interference caused by overlapping installation nodes.

[0005] Furthermore, the lack of cross-industry data standards and insufficient data collaboration have exacerbated the chaotic configuration, resulting in poor compliance of deployment resource management and high collaboration costs, which seriously restricts the standardization and large-scale implementation of the "one tower for multiple uses" model.

[0006] Against this backdrop, there is an urgent need to build a resource allocation system for laying out resources based on three-dimensional model analysis, quantitative calculation, intelligent screening, and dynamic optimization. This system can solve the problems of inaccurate total estimation, inefficient process screening, and unreasonable node layout in traditional solutions, and achieve accurate allocation, efficient utilization, and safe and compliant management of laying out resources. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides an intelligent optimization and allocation system for power pole installation resources. This system solves the problem of mismatch between the total installation volume and actual demand caused by the failure to quantitatively calculate the three-dimensional structural characteristics of power poles and the spatial distribution of mounting points.

[0008] To achieve the above objectives, the present invention provides the following technical solution: an intelligent optimization allocation system for power pole installation resources, comprising:

[0009] The associated model processing end acquires a 3D model of the power poles and, based on the marked pole location points within the 3D model, confirms the area characteristics associated with several pole location points. Then, based on the associated range set for communication installations, it determines the range of the total number of installations. The specific method is as follows:

[0010] Identify the marked pole locations within the 3D model of power poles. Based on the specific location and adjacent features of the pole locations, connect adjacent pole locations. The connecting lines represent the straight-line distance between adjacent pole locations. Repeat this process for several pole locations to generate a topology map of the connections between them.

[0011] Based on the marked connection topology, connect several outer tower locations to confirm the closed shape of the connection topology and identify the area M associated with the closed shape. Then extract the associated range F set for the installation, where F is a preset value. Use M÷F=Tz to confirm the feature value Tz. Use (1.2×Tz) and (1.5×Tz) to confirm two sets of range values. Round the two sets of range values ​​to confirm the integer value associated with the corresponding range value.

[0012] Based on the two confirmed sets of integer values, generate the total number of installations associated with the installation, with the endpoints of the interval being the two confirmed sets of integer values;

[0013] The installation process processing end, based on the determined range of the total number of installations and the marked connection topology, executes several installation processing processes. Installation processes that achieve the coverage target are recorded as qualified processes, and the optimal process is locked from among the qualified processes. Specifically:

[0014] Based on the determined range of total number of installations, the installation parameter C is selected gradually from the minimum value of the range to the maximum value.

[0015] Based on the selected installation parameter C, within the marked connection topology, a total number of mounting points corresponding to the total number are randomly selected, and each group of tower locations is assigned a communication installation. Based on the associated range set by the communication installation, the connection topology is marked, and the proportion of the total area of ​​the closed shape of the entire connection topology is identified. The total area covered by the associated range is confirmed and marked as M1. Based on the area M of the closed shape, it is determined whether the current installation assignment process satisfies: (M1÷M)≥95%. If it satisfies, the current associated installation assignment process is marked as a qualified process; otherwise, no marking is performed. After the current installation assignment process is completed, the installation assignment process is performed on different mounting points in sequence. In each process, the associated mounting points are not repeated.

[0016] Select the installation parameters from the range of the total number of installations, execute the corresponding installation assignment process, and lock the qualified process from the several sets of installation assignment processes executed, and perform relevant calibration.

[0017] The specific locking method for the optimal process is as follows:

[0018] The overall area percentage associated with each group of achievement processes is confirmed and marked as Zm. i , where i represents different achievement processes, and then the associated range of different applications in each achievement process is marked, the cross range between different associated ranges is identified, and the proportion of the corresponding cross range located in the associated range is recorded. This proportion is used as the range feature of two sets of associated ranges that have an overlap. Then, the range features of different types of associated ranges that have an overlap are confirmed in turn, and the confirmed range features are summed to obtain the total range feature value Zh.

[0019] Using: (Zm) i ÷Zh) = process characteristics, and confirm the process characteristics associated with each qualified process in turn. From the confirmed sets of process characteristics, select the maximum value, and record the qualified process associated with the maximum value as the optimal process. Then, transmit the confirmed optimal process to the optimization end of the mounting node.

[0020] The installation node optimization end, based on the identified optimal process, determines the position of each installation node, and based on the associated range of each installation node, identifies overlapping installation nodes. It then dynamically optimizes and adjusts these overlapping installation nodes, completing the specific optimization and adjustment process for the optimal process. The specific method is as follows:

[0021] From the optimal process, identify the location of each laying node, and based on the associated range of the laying nodes, identify two groups of laying nodes with overlapping ranges, and the two groups of laying nodes do not have overlapping ranges with other laying nodes, only the two groups of laying nodes have overlapping ranges.

[0022] Identify the location points of the two sets of mounting nodes, simultaneously record the adjacent mounting points of the location points as undetermined points, record the identified location points as end points, and simultaneously identify the associated center points within the intersection range. Using the center point as the starting point, confirm the direction of the line connecting the starting point to the end point, and perform extension processing based on this line direction to confirm the extension line. Identify the set of undetermined points with the smallest vertical distance from the extension line, and record this undetermined point as the selected point.

[0023] The selected points associated with the two sets of laying nodes are confirmed sequentially. First, one set of laying nodes is adjusted to the position of the associated selected point, and the process characteristics of the optimal process are reconfirmed. It is identified whether the process characteristic value has decreased. If it has decreased, the current optimization process is recorded and the laying nodes of the optimal process are adjusted synchronously. If it has not decreased, the other set of laying nodes is adjusted to the position of the associated selected point, and the process characteristic value is identified again to see if it has decreased, and the corresponding optimization process is recorded.

[0024] The two sets of installation nodes with overlapping ranges are optimized sequentially, and the corresponding optimization process is recorded. The optimal process after optimization is output through the output terminal for external relevant personnel to view.

[0025] This invention provides an intelligent optimization allocation system for power pole installation resources. Compared with existing technologies, it has the following advantages:

[0026] This invention uses the "coverage ratio ≥ 95%" as the core standard to screen qualified processes through the installation process processing terminal, and locks the optimal process through the comprehensive calculation of "area ratio and cross-range ratio". This ensures that the communication installation covers the entire coverage area of ​​the tower, and minimizes the invalid cross-over between installations.

[0027] For overlapping cable routing nodes in the optimal process, a dynamic adjustment mechanism of "adjacent undetermined point identification + connection direction extension + process feature verification" effectively reduces the overlap range between communication cables. While ensuring comprehensive coverage, this allows each routing node to fully play its role, improving the utilization rate of routing point resources. Simultaneously, the optimized routing node layout better meets cable safety spacing requirements, reduces interference risks caused by dense crossover of communication cables, and aligns with the quality control requirements of cross-industry safety standards and data governance systems. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the principle framework of the present invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0030] Please see Figure 1 This application provides an intelligent optimization and allocation system for power pole installation resources, including an association model processing end, an installation process processing end, an installation node optimization end, and an output terminal, wherein the association model processing end, the installation process processing end, the installation node optimization end, and the output terminal are electrically connected from the output node to the input node in sequence.

[0031] The associated model processing end acquires a three-dimensional model of the power poles and, based on the marked pole locations within the model, confirms the area characteristics associated with several pole locations. Then, based on the associated range set for communication installation, it determines the range of the total number of installations and transmits this information to the installation process processing end. Specifically, for each marked pole location in the three-dimensional model, there are multiple mounting points. Here, for a single pole location, only a single communication installation is performed. After each pole location is connected to the others, a mounting topology map associated with several pole locations is formed. Based on the area confirmation process, the numerical range of the total number of installations is identified, and thus, the installation process is comprehensively performed.

[0032] The specific method for determining the range of the total number of installations is as follows:

[0033] Identify the marked pole locations within the 3D model of power poles. Based on the specific location and adjacent features of the pole locations, connect adjacent pole locations. The connecting lines represent the straight-line distance between adjacent pole locations. Repeat this process for several pole locations to generate a topology map of the connections between them.

[0034] Based on the marked connection topology map, connect several outer tower locations to confirm the closed shape of the connection topology map, identify the area M associated with the closed shape, and then extract the associated range F set for the installation. F is a preset value, and its specific value is determined by the operator based on experience. The characteristic value Tz is confirmed by M÷F=Tz. The two range values ​​are confirmed by (1.2×Tz) and (1.5×Tz). The two range values ​​are rounded to confirm the integer value associated with the corresponding range value.

[0035] Based on the two confirmed integer values, a range of the total number of hangs associated with the hangs is generated, with the endpoints of the range being the two confirmed integer values. Specifically, this processing method can effectively control the total number of hangs and, based on the subsequent specific hanging process, rationally plan the total number of hangs so that several hangs can effectively cover the corresponding connection topology, thereby achieving the optimal hanging effect.

[0036] Among them, the laying process processing end executes several laying processes based on the determined range of the total number of laying processes and the marked connection topology map. The laying process that meets the coverage target is recorded as the target process, and the optimal process is locked from the target process and transmitted to the laying node optimization end.

[0037] The specific method for identifying compliant processes in the application process processing end is as follows:

[0038] Based on the determined range of total number of installations, the installation parameter C is selected gradually from the minimum value of the range to the maximum value.

[0039] Based on the selected installation parameter C, within the marked connection topology, a total number of pole locations are randomly selected, and each group of pole locations is assigned a communication installation. Based on the associated range (i.e., the communication coverage range) set by the communication installation, it is marked within the connection topology. The proportion of the overall area of ​​the closed shape of the entire connection topology is identified, and the total area covered by the associated range is confirmed and marked as M1. Based on the area M of the closed shape, it is determined whether the current installation assignment process satisfies: (M1÷M)≥95%. If it satisfies, the current associated installation assignment process is marked as a qualified process; otherwise, no marking is performed. After the current installation assignment process is completed, the installation assignment process is performed on different mounting points in sequence. In each process, the associated mounting points are not repeated.

[0040] Then, select the installation parameters from the total number of installations in sequence, execute the corresponding installation assignment process, and lock the qualified process from the several sets of installation assignment processes executed, and perform relevant calibration.

[0041] Specifically, the determined total number of installations is set to [12, 20]. Installation parameter 12 is selected first to execute the corresponding installation assignment process. 12 pole locations are selected in the corresponding connection topology map, and several selection processes are executed. Each selection process does not repeat the pole location. The installation range associated with each pole location is then marked. From the marked range coverage process, the specific proportion of the range area in the overall topology map area is identified, thereby identifying the compliant process. The optimal process is then selected from the marked compliant processes.

[0042] The specific locking method for the optimal process is as follows:

[0043] The overall area percentage associated with each group of achievement processes is confirmed and marked as Zm. i , where i represents different achievement processes, and then the associated range of different applications in each achievement process is marked, the cross range between different associated ranges is identified, and the proportion of the corresponding cross range located in the associated range is recorded. This proportion is used as the range feature of two sets of associated ranges that have an overlap. Then, the range features of different types of associated ranges that have an overlap are confirmed in turn, and the confirmed range features are summed to obtain the total range feature value Zh.

[0044] Using: (Zm) i ÷Zh) = process characteristics, and confirm the process characteristics associated with each qualified process in turn. From the confirmed sets of process characteristics, select the maximum value, and record the qualified process associated with the maximum value as the optimal process. Then, transmit the confirmed optimal process to the optimization end of the mounting node.

[0045] Specifically, each group of compliant processes has a corresponding total area in the topology map. Each placement location is associated with a corresponding placement range, and there are overlapping ranges between each placement range. The overlapping ranges have specific range percentages. By summing the confirmed range percentages, the total range percentage value is determined. If the total range percentage value is larger, the confirmed process characteristic will be smaller, and vice versa. From this processing method, the optimal process can be selected from the confirmed multiple groups of compliant processes for subsequent optimization.

[0046] Among them, the laying node optimization end, based on the marked optimal process, confirms the position of each laying node, and based on the associated range of the laying node, confirms the overlapping laying nodes, and dynamically optimizes and adjusts the overlapping laying nodes, completes the specific optimization and adjustment process of the optimal process, and displays it through the output terminal.

[0047] The specific method for dynamically optimizing and adjusting overlapping installation nodes is as follows:

[0048] From the optimal process, identify the location of each laying node, and based on the associated range of the laying nodes, identify two groups of laying nodes with overlapping ranges, and the two groups of laying nodes do not have overlapping ranges with other laying nodes, only the two groups of laying nodes have overlapping ranges.

[0049] Identify the location points of the two sets of installation nodes, and simultaneously record the adjacent installation points of the location points as undetermined points (if the installation points are already installed, the calibration process of undetermined points will not be performed). Record the identified location points as end points, and simultaneously identify the associated center points within the intersection range. Using the center point as the starting point, confirm the direction of the line connecting the starting point to the end point, and perform extension processing based on this line direction to confirm the extension line. Identify the set of undetermined points with the smallest vertical distance from the extension line, and record this undetermined point as the selected point.

[0050] The selected points associated with the two sets of laying nodes are confirmed sequentially. First, one set of laying nodes is adjusted to the position of the associated selected point, and the process characteristics of the optimal process are reconfirmed. It is identified whether the process characteristic value has decreased. If it has decreased, the current optimization process is recorded and the laying nodes of the optimal process are adjusted synchronously. If it has not decreased, the other set of laying nodes is adjusted to the position of the associated selected point, and the process characteristic value is identified again to see if it has decreased, and the corresponding optimization process is recorded.

[0051] Similarly, the two sets of installation nodes with overlapping ranges are optimized in turn, and the corresponding optimization process is recorded. The optimal process after optimization is output through the output terminal for external relevant personnel to view.

[0052] Specifically, after the corresponding mounting nodes are determined, the remaining mounting points associated with the corresponding connection diagram are used to make adaptive adjustments to the mounting nodes through optimization and adjustment. This reduces the intersection range between different mountings, thereby fully reducing the coverage of the connection topology diagram by different mountings, so that the corresponding mounting processing process reaches the optimal state and the mounting resources can be used rationally.

[0053] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0054] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A smart optimization allocation system for power pole installation resources, characterized in that, include: The associated model processing end acquires a 3D model of the power poles and, based on the marked pole location points within the 3D model, confirms the area characteristics associated with several pole location points. Then, based on the associated range set for communication installations, it determines the range of the total number of installations. The specific method is as follows: Identify the marked pole locations within the 3D model of power poles. Based on the specific location and adjacent features of the pole locations, connect adjacent pole locations. The connecting lines represent the straight-line distance between adjacent mounting points. Identify and process several mounting points sequentially to generate a topology map of the connections between these mounting points. Based on the marked connection topology, connect several outer tower locations to confirm the closed shape of the connection topology and identify the area M associated with the closed shape. Then extract the associated range F set for the installation, where F is a preset value. Use M÷F=Tz to confirm the feature value Tz. Use 1.2×Tz and 1.5×Tz to confirm two sets of range values. Round the two sets of range values ​​to confirm the integer value associated with the corresponding range value. Based on the two confirmed sets of integer values, generate the total number of installations associated with the installation, with the endpoints of the interval being the two confirmed sets of integer values; The installation process processing end executes several installation processes based on the determined range of the total number of installations and the marked connection topology map. The installation process that achieves the coverage target is recorded as the target process, and the optimal process is locked from the target process. The installation node optimization end, based on the identified optimal process, confirms the location of each installation node, and based on the associated range of the installation node, identifies overlapping installation nodes, and dynamically optimizes and adjusts the overlapping installation nodes to complete the specific optimization and adjustment process of the optimal process.

2. The intelligent optimization allocation system for power pole installation resources according to claim 1, characterized in that, The specific method by which the application process processing terminal identifies the compliant process is as follows: Based on the determined range of total number of installations, the installation parameter C is selected gradually from the minimum value of the range to the maximum value. Based on the selected installation parameter C, within the marked connection topology diagram, a total number of mounting points corresponding to the total number are randomly selected, and each group of mounting points is assigned an installation. Based on the association range set by the communication installation, the connection topology diagram is marked, and the overall area ratio of several association ranges in the closed shape of the entire connection topology diagram is identified. The total area covered by several association ranges is confirmed and marked as M1. Based on the area M of the closed shape, it is determined whether the current installation assignment process satisfies: (M1÷M)≥95%. If it satisfies, the current associated installation assignment process is marked as a qualified process; otherwise, no marking is performed. After the current installation assignment process is completed, the installation assignment process is carried out sequentially for different tower locations. In each process, the associated mounting points are not repeated.

3. The intelligent optimization allocation system for power pole installation resources according to claim 2, characterized in that, The specific methods for identifying the compliant process in the application process processing terminal also include: Select the installation parameters from the range of total installations, execute the corresponding installation assignment process, and lock the qualified process from the several sets of installation assignment processes executed, and perform relevant calibration.

4. The intelligent optimization allocation system for power pole installation resources according to claim 2, characterized in that, The specific method for locking the optimal process in the application process processing terminal is as follows: The overall area percentage associated with each group of achievement processes is confirmed and marked as Zm. i , where i represents different achievement processes, and then the associated range of different applications in each achievement process is marked, the cross range between different associated ranges is identified, and the proportion of the corresponding cross range located in the associated range is recorded. This proportion is used as the range feature of two sets of associated ranges that have an overlap. Then, the range features of different types of associated ranges that have an overlap are confirmed in turn, and the confirmed range features are summed to obtain the total range feature value Zh. Using: (Zm) i ÷Zh) = process characteristics, and confirm the process characteristics associated with each qualified process in turn. From the confirmed groups of process characteristics, select the maximum value, and record the qualified process associated with the maximum value as the optimal process. Then, transmit the confirmed optimal process to the optimization end of the mounting node.

5. The intelligent optimization allocation system for power pole installation resources according to claim 1, characterized in that, The specific method for dynamically optimizing and adjusting intersecting laying nodes in the aforementioned laying node optimization end is as follows: From the optimal process, identify the location of each laying node, and based on the associated range of the laying nodes, identify two groups of laying nodes with overlapping ranges, and the two groups of laying nodes do not have overlapping ranges with other laying nodes, only the two groups of laying nodes have overlapping ranges. Identify the location points of the two sets of mounting nodes, simultaneously record the adjacent mounting points of the location points as undetermined points, record the identified location points as end points, and simultaneously identify the associated center points within the intersection range. Using the center point as the starting point, confirm the direction of the line connecting the starting point to the end point, and perform extension processing based on this line direction to confirm the extension line. Identify the set of undetermined points with the smallest vertical distance from the extension line, and record this undetermined point as the selected point. The selected points associated with the two sets of laying nodes are confirmed sequentially. First, one set of laying nodes is adjusted to the position of the associated selected point, and the process characteristics of the optimal process are reconfirmed. It is identified whether the process characteristic value has decreased. If it has decreased, the current optimization process is recorded and the laying nodes of the optimal process are adjusted synchronously. If it has not decreased, the other set of laying nodes is adjusted to the position of the associated selected point, and the process characteristic value is identified again to see if it has decreased, and the corresponding optimization process is recorded.

6. The intelligent optimization allocation system for power pole installation resources according to claim 1, characterized in that, The specific methods for dynamically optimizing and adjusting intersecting laying nodes in the aforementioned laying node optimization end also include: The two sets of installation nodes with overlapping ranges are optimized sequentially, and the corresponding optimization process is recorded. The optimal process after optimization is output through the output terminal for external relevant personnel to view.

Images