Open-pit mine 5G base station oil-electric hybrid power supply method and system

Abstract

The application discloses an open-pit mine 5G base station oil-electricity hybrid power supply method and system, relates to the technical field of open-pit mine base station power supply, and mainly comprises the following steps: determining a mine area network coverage range, performing effective communication area division, obtaining a plurality of first target areas, analyzing the characteristics of communication objects contained in each first target area, obtaining a plurality of characteristic distribution results, and generating a characteristic distribution matrix diagram; determining a communication base station matching strategy based on each characteristic distribution matrix diagram, and performing labeling processing on the matched plurality of communication base stations respectively; extracting the attribute labels of each communication base station, performing correlation measurement processing on all the attribute labels of the communication base station, and obtaining an indication output result; and selecting a power supply mode of the base station based on the indication output result. The power supply method and system can make each base station adapt to the communication characteristics of the communication objects in the area, thereby strategically selecting the power supply mode, and guaranteeing better power supply matching and power rational utilization.

Description

Technical Field

[0001] This invention relates to the field of power supply technology for open-pit mine base stations, and more specifically, to a hybrid power supply method and system for 5G base stations in open-pit mines using oil and electricity. Background Technology

[0002] To promote the integration of intelligent technologies with the coal industry, smart mine demonstration projects have been gradually and systematically implemented. Key planned projects in smart mines include unmanned driving equipment, remote monitoring equipment, and continuous mining equipment, all of which require high-bandwidth, low-latency communication networks for data and signal transmission. Therefore, deploying 5G communication base stations in open-pit mines can effectively meet the high data transmission capacity, low latency, and high reliability requirements of the mining area, thereby enabling the integration and sharing of business data within the mining environment.

[0003] In current smart mines, 5G base stations are deployed at different locations within the mining area based on actual communication needs. However, the power supply modes for all 5G base stations are relatively uniform, such as relying solely on mains power, battery-powered power, or fuel-powered generators. This leads to insufficient power supply management and wasted power resources. One specific reason for this is that the communication equipment in mines operates under different conditions, including continuous low-voltage power supply, intermittent high-voltage power supply, and AC / DC power supply. Therefore, using the same power supply mode for all communication equipment can easily result in mismatches between power supply targets, leading to the unreasonable utilization of power resources.

[0004] In view of the above, this application is hereby submitted. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for hybrid power supply of 5G base stations in open-pit mines. This power supply method and system effectively divides the network coverage area of ​​the mining area into communication zones. This division is based on the characteristics of communication objects within the reference zone to match communication base stations, so that each base station can adapt to the communication characteristics of the communication objects in the area. This allows for strategic selection of power supply modes, ensuring better power supply matching and rational utilization of electricity.

[0006] The embodiments of the present invention are implemented as follows:

[0007] Firstly, a hybrid power supply method for 5G base stations in open-pit mines, comprising the following steps:

[0008] The network coverage area of ​​the mining area is determined, and the effective communication area is divided based on the network coverage area to obtain multiple first target areas. The effective communication area refers to the area that meets the communication requirements of the specified area.

[0009] Analyze the characteristics of the communication objects contained in each first target region to obtain multiple characteristic distribution results, and generate a characteristic distribution matrix based on these multiple characteristic distribution results;

[0010] Based on the distribution matrix of each feature, a matching strategy for communication base stations is determined. The matched communication base stations are then labeled. Labeling refers to analyzing the attributes of the communication base stations to obtain multiple attribute labels.

[0011] Extract the attribute labels of each communication base station, perform correlation measurement on all attribute labels of the communication base station, and obtain the indication output result;

[0012] The power supply mode of the base station is selected based on the output result of the indication. The power supply mode includes fuel power supply mode and / or battery power supply mode.

[0013] In an optional implementation, dividing the effective communication area based on the network coverage to obtain multiple first target areas includes the following steps:

[0014] Obtain multiple boundary parameters of the network coverage area, and determine the center parameter of the network coverage area based on the multiple boundary parameters;

[0015] Obtain the Euclidean distance between each boundary parameter and the center parameter, and calculate and obtain the mean value based on all obtained Euclidean distances;

[0016] Multiple boundary target regions are divided using a single boundary parameter as an arc point and the mean value as the radius. The multiple boundary target regions are then subjected to compensation transformation to determine the central target region. All boundary target regions and all central target regions together form multiple first target regions.

[0017] In an optional implementation, the following steps are included before determining the network coverage area of ​​the mining area:

[0018] Collect resource coverage distribution information maps of the mining area, and determine the original exploration and mining scope and the target exploration and mining scope based on the resource coverage distribution information maps;

[0019] Calculate the distribution of the difference between the original exploration and mining area and the target exploration and mining area, and establish a dynamic mining plan table;

[0020] The operational area is updated in real time based on the dynamic mining plan, and the coverage area of ​​the mining network is determined according to the operational area.

[0021] In an optional implementation, performing compensation transformation on multiple boundary target regions to determine the central target region includes the following steps:

[0022] Based on concentricity, multiple boundary target regions are rotated in a compensatory manner to form a boundary enclosed region; the central blank range of the boundary enclosed region is marked, and the central blank range is analyzed and compared with the spatial range divided by the central parameter and the mean value result to obtain the first analysis result; the distribution of the central target region is determined based on the first analysis result.

[0023] In an optional implementation, after dividing multiple boundary target regions using a single boundary parameter as an arc point and the mean value as the radius, the following steps are further included:

[0024] Obtain the set of difference distributions of all Euclidean distances and mean values, and integrate the subset of difference distributions that meet the first preset threshold into the second analysis result;

[0025] The distribution of the boundary target region is formed by adjusting the corresponding boundary parameters based on the second analysis results.

[0026] In an optional implementation, the characteristics of the communication object include: data transmission type, object movement range, data communication latency, and broadband rate;

[0027] Analyzing the characteristics of the communication objects contained in each first target region to obtain multiple characteristic distribution results includes the following steps:

[0028] In each first target area, the communication objects are classified according to the same characteristic to obtain multiple characteristic classification sets;

[0029] Calculate the proportion and priority of each feature classification set, generate feature correlation coefficients, and extract the feature correlation coefficients that meet the second preset threshold as the feature distribution results.

[0030] In an optional implementation, determining a communication base station matching strategy based on each characteristic distribution matrix diagram, and then labeling the matched communication base stations respectively, includes the following steps:

[0031] Determine the distance correlation between the distribution results of each characteristic in the characteristic distribution matrix, obtain multiple distance correlation distribution results, and select the distance correlation distribution result that meets the third preset threshold as the reference basic quantity;

[0032] The type and distribution location of communication base stations are selected based on reference basic quantities, thereby determining the communication base station matching strategy;

[0033] For the matched communication base stations, extract the reference basic quantity belonging to the communication base station again, and decompose the reference basic quantity into multiple corresponding characteristic distribution results as their attribute labels.

[0034] In an optional implementation, after extracting the characteristic correlation coefficients that satisfy the second preset threshold as the characteristic distribution result, the following steps are further included:

[0035] Calculate the difference between the correlation coefficient of each characteristic that does not meet the second preset threshold requirement and the second preset threshold, and arrange all the differences in ascending order of absolute value to generate a difference distribution sequence;

[0036] Determine the mean scalar of all distance-related distribution results, and obtain the span between the mean scalar and the third preset threshold;

[0037] The characteristic correlation coefficients corresponding to the difference distribution sequence are extracted according to the span as the step size distance, and the compensation is used as the characteristic distribution result.

[0038] In an optional implementation, the correlation measurement processing of all attribute labels of the communication base station to obtain the indication output result includes the following steps:

[0039] Extract key information from each attribute tag, generate node information clusters, and perform category classification on the node information clusters to obtain multiple classification sets;

[0040] Extract the categories that meet the preset requirements and merge them into the output result.

[0041] Secondly, an open-pit mine 5G base station hybrid power supply system includes:

[0042] The first determining unit is used to determine the network coverage area of ​​the mining area and to divide the effective communication area based on the network coverage area to obtain multiple first target areas;

[0043] The first analysis unit is used to analyze the characteristics of the communication objects contained in each first target area, obtain multiple characteristic distribution results, and generate a characteristic distribution matrix based on the multiple characteristic distribution results;

[0044] The first labeling unit is used to determine the communication base station matching strategy based on each feature distribution matrix diagram, and to label the matched communication base stations respectively. The labeling process refers to analyzing the attributes of the communication base stations to obtain multiple attribute labels.

[0045] The first calculation unit is used to extract the attribute labels of each communication base station, perform correlation measurement processing on all attribute labels of the communication base station, and obtain the indication output result.

[0046] The first strategy unit is used to select the power supply mode of the base station based on the indication output result, wherein the power supply mode includes fuel power supply mode and / or battery power supply mode.

[0047] The beneficial effects of the embodiments of the present invention are:

[0048] The oil-electric hybrid power supply method and system for 5G base stations in open-pit mines provided in this invention firstly divides the network coverage area of ​​the mining area into multiple first target areas that can meet the communication requirements of the corresponding areas. Then, by analyzing the communication characteristics of the communication objects in each first target area, communication base stations that can meet the corresponding communication requirements or standards are matched based on the communication characteristics or features. Finally, the correct power supply mode is determined according to the different power supply duration, voltage level and demand patterns of different types of communication base stations, thereby replacing the traditional single power supply mode. This effectively solves the problem of unreasonable use of power supply resources caused by mismatch of power supply objects, and realizes strategic power supply mode selection in the mining area, which can ensure better power supply matching and rational use of electricity.

[0049] Overall, the oil-electric hybrid power supply method and system for 5G base stations in open-pit mines provided by the embodiments of the present invention integrates the characteristics of open-pit mines themselves, namely, the inability to achieve a single power supply mode, especially when it is difficult to access the mains power. It rationally selects the mode of oil-fired power supply and / or electric storage power supply, so that the power or electricity in the mining area can not only match the usage needs of the electricity users, but also achieve reasonable management and distribution of electricity, which has certain application and promotion significance. Attached Figure Description

[0050] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0051] Figure 1 A flowchart illustrating the main steps of the power supply method provided in this embodiment of the invention;

[0052] Figure 2 for Figure 1 The flowchart of a sub-step of one of the main steps, S200, is shown.

[0053] Figure 3 for Figure 1 The flowchart of a sub-step of one of the main steps, S100, is shown.

[0054] Figure 4 for Figure 2 The flowchart of a sub-step of step S230 shown in the steps is as follows.

[0055] Figure 5 for Figure 1 The flowchart shows a sub-step of one of the main steps, S300.

[0056] Figure 6 for Figure 1 The flowchart shows a sub-step of one of the main steps, S400.

[0057] Figure 7 for Figure 1 The flowchart shows a sub-step of one of the main steps, S500.

[0058] Figure 8 An exemplary module diagram of a power supply system provided in an embodiment of the present invention. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0060] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0061] It should be understood that the terms "system," "device," and / or "module" used in this invention are methods for distinguishing different components, elements, parts, sections, or assemblies at different levels. However, if other terms can achieve the same purpose, they may be replaced by other expressions.

[0062] As indicated in this invention and the claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0063] Flowcharts are used in this invention to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, the steps can be processed in reverse order or simultaneously. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.

[0064] Please see Figure 1This embodiment provides a hybrid oil-electric power supply method for 5G base stations in open-pit mines, mainly used to achieve reasonable and effective power supply for communication base stations in open-pit mines. This method combines the communication characteristics of the working objects in the open-pit mine for matching power supply, achieving good power supply matching and rational power utilization. Specifically, the power supply method includes the following steps:

[0065] S200: Determine the network coverage area of ​​the mining area and, based on this network coverage area, divide the area into effective communication zones to obtain multiple first target zones. The effective communication zone refers to the area that meets the communication requirements of a specified area. This step is mainly used to divide the communication zones. Considering that the intelligent mining area itself needs to determine the coverage area of ​​the communication network in advance to ensure that all communication devices within it can meet normal communication requirements, and that communication devices generally require different communication waves, this will inevitably affect the choice of power supply, the network coverage area is further divided into multiple sub-communication zones, i.e., the first target zones. It should be noted that the network coverage area is not entirely equivalent to the effective communication zone. Since the effective communication zone needs to meet the communication requirements of the area where the mining area is located, generally speaking, the network coverage area is larger than the effective communication zone.

[0066] The criteria for dividing each first target area (sub-communication area) can be, for example, based on the pre-planned design of the mining area, determining which part of the mining area's development operations each area will primarily handle, and thus dividing the effective communication area accordingly. Alternatively, it can be based on the mining area's budget requirements, optimizing the location and number of base stations to roughly determine their distribution, and then pre-planning and dividing the effective communication area accordingly. Another example is based on the terrain characteristics, considering whether they will excessively impact communication quality and operational development, thus dividing the effective communication area with the aim of minimizing such impact. It should be noted that the resulting multiple first target areas after the above-mentioned effective communication area division must meet the communication requirements of the sub-areas, and adjacent first target areas can be adjacent or overlap, primarily ensuring communication across all sub-areas.

[0067] After dividing the target area into multiple primary target areas, the communication requirements of each area are not entirely the same. To identify the differences in communication requirements or needs, step S300 is performed based on the characteristics of the communication objects. Specifically, this involves analyzing the characteristics of the communication objects contained in each primary target area, obtaining multiple characteristic distribution results, and generating a characteristic distribution matrix based on these results. Through the above steps, the planned or future communication objects in each primary target area are collected and statistically analyzed. Communication objects of the same category are analyzed, and their communication characteristics are listed as their communication features. After combining the communication features of all categories of communication objects, i.e., the multiple characteristic distribution results, they are integrated into a characteristic distribution matrix, thereby providing a clear picture of the approximate communication needs of the primary target area. Generally, if there are changes in the planning of future communication objects or if the planning is highly uncertain, the analysis can also be based on the established communication objects.

[0068] Taking typical communication objects in a smart mining area as examples, such as unmanned mining trucks, their communication characteristics are: 0.3Mbps uplink and 0.5Mbps downlink for control services per unit, and 30Mbps uplink for video per vehicle, totaling approximately 30.3Mbps uplink and 0.5Mbps downlink per vehicle, with a latency of less than 20ms; the communication characteristics of remote control equipment for electric shovels are 80Mbps uplink and 10Mbps downlink, with a latency of less than 20ms; the communication characteristics of collaborative operation auxiliary equipment are 4Mbps uplink and 2Mbps downlink, with a latency of less than 20ms; the communication characteristics of auxiliary remote operation equipment are 100Mbps uplink and 10Mbps downlink, with a latency of less than 20ms; the communication characteristics of continuous coal mining equipment are a latency of ≤20ms and an uplink edge rate of not less than 300Mbps; the communication characteristics of pit drainage and power supply equipment are 50Mbps uplink and 10Mbps downlink, with a latency of less than 20ms. The above are just some examples of the communication characteristics of typical target equipment, intended to facilitate the understanding of the technical solution of this step by those skilled in the art.

[0069] After analyzing all communication characteristics, multiple characteristic distribution results can be obtained. A column of characteristic results is established for each category of communication characteristics. By combining the results of all categories of characteristics, a characteristic distribution matrix diagram, or characteristic distribution matrix table, can be constructed. Obtaining this characteristic distribution matrix diagram allows for the communication base station determination step S400. Specifically, a communication base station matching strategy is determined based on each characteristic distribution matrix diagram. The matched communication base stations are then labeled. This labeling process involves analyzing the attributes of the communication base stations to obtain multiple attribute labels. Through these steps, a characteristic distribution matrix diagram is established for each first target area. Based on the width and depth of the characteristic distribution matrix, a communication base station capable of covering all coordinate communication characteristics is selected. Since this communication base station is a key device for carrying all communication characteristics in this sub-area, analyzing the selected communication base station as the basis is more effective. Therefore, each matched communication base station is labeled, and its characteristics are analyzed, especially the attributes related to changes in power supply or synchronous power changes due to changes in communication requirements or modes. All attributes are integrated into attribute labels and assigned to the communication base station.

[0070] For example, a selected communication base station can effectively improve user experience. Communication parameters include 2.6GHz 100M+4.9GHz, 100M cross-carrier CA scenario, meeting the needs of enhanced uplink and downlink capacity in ultra-high traffic areas; and 2.6GHz 100M+700M 30MCA scenario, significantly improving cell coverage. The central 2T4R user base supports 2.6GHz dual-stream, the midpoint supports 2.6GHz+700MHz concurrent operation, and the far point uses 700MHz to improve uplink experience, further increasing uplink capacity (20%–60% for near points, 200%–400% for far points). These communication parameters can be used to extract attribute tags, thus completing the tagging process.

[0071] After labeling the matched communication base stations, all assigned attribute tags are filtered to obtain a de-filtered result as a reference for power supply selection. Specifically, step S500 involves extracting the attribute tags of each communication base station, performing correlation measurement on all attribute tags, and obtaining an indication output result. Through these steps, it is understood that each communication base station has numerous attribute tags, some of which are relatively discrete, meaning they do not belong to the same category in terms of power supply significance as other attribute tags. Therefore, filtering is necessary, using the category represented by the majority of attribute tags as a reference, and obtaining an indication output result to achieve a more accurate and effective selection of the power supply mode. Then, step S600 is executed to select the power supply mode of the base station based on the indication output result. The power supply mode includes fuel-powered mode and / or battery-powered mode. This means that because the communication modes of the base stations are different, the power supply mode is determined based on the communication mode represented by the indication output result. For example, if high-bandwidth, continuous communication is required, a combined fuel-powered and battery-powered mode can be considered; or, if high-capacity, stable communication is required, a battery-powered mode can be considered.

[0072] It is understandable that fuel-powered power supply mode mainly refers to using a fuel engine to drive a generator to provide AC power or converted DC power, while energy storage power supply mode mainly refers to using stored electrical energy after generation or charging for direct power supply. Regardless of the power supply mode used, the basic principle is to select based on the power consumption requirements and changes in power consumption of the communication base station. When there is continuous high power output, fuel-powered power supply mode is preferred to ensure high power consumption requirements. On the basis of fuel-powered power supply mode, charging and discharging energy storage operations can be carried out to continuously supplement fuel supply during periods of fuel supply stagnation. When power consumption is relatively low and a stable supply is required, energy storage power supply mode is preferred to ensure power demand. Especially when power consumption is generally reduced, the use of cyclically charged and discharged energy storage batteries can ensure power supply, avoiding peak power consumption periods and achieving further rational utilization of electricity.

[0073] Through the technical solution formed by the above steps S200-S600, the characteristics of communication equipment in the mining area are effectively collected and analyzed. Based on this, the selection of communication base stations not only meets the communication needs of the sub-area, but also has prominent characteristics that are easy to distinguish. Targeted and matched power supply is carried out for different types of communication base stations to achieve strategic power supply, thereby ensuring good power supply matching and rational utilization of electricity.

[0074] In some embodiments, considering that the development area of ​​a mining area is constantly changing as it is continuously developed, this will cause changes in network coverage, which in turn will cause changes in the division of the first target area. Specifically, please refer to... Figure 3Before determining the network coverage area of ​​the mining area, step S100 is included, which includes the following sub-steps:

[0075] S110: Collect a resource coverage distribution information map of the mining area, and determine the original exploration and mining scope and the target exploration and mining scope based on the resource coverage distribution information map. By pre-exploring the resource coverage of the mining area, the basic area and scope involved in mining or development are determined. From this target mining scope, the initial excavation coverage scope and the excavation coverage scope at the end of each stage are determined. This indicates that the development scope involved in the mining operation is in a dynamic change range. During this dynamic change process, the original exploration and mining scope and the target exploration and mining scope are determined, which is the next step, S210.

[0076] S120: Calculate the distribution of the difference between the original exploration and mining area and the target exploration and mining area, and establish a dynamic mining plan table. Since the original and target areas have varying geographical boundaries, the target area always covers the original area, but the extended area may exist in different locations within the original area. Therefore, it is necessary to delineate the extended boundaries based on the differences in boundary distribution. Then, according to the proposed mining plan, the time dimension of the mining is added to establish a dynamic mining plan table. This dynamic mining plan table mainly indicates the time period during which mining operations will be carried out in the extended area. Afterwards, proceed to step S130.

[0077] S130: Update the work area range in real time based on the dynamic mining plan, and determine the network coverage range of the mining area according to the work area range. This step indicates that after executing according to the dynamic mining plan, it is necessary to continuously expand and update the work area range. This work area range mainly refers to the overall area constituted by the scope of communication equipment involved in the mining operation. As the range of this area is continuously expanded, the network coverage range of the mining area can be determined in real time. Through steps S110-S130, the network coverage range required by the communication equipment can be determined in real time and with accuracy, taking into account the constantly changing characteristics of the mining area. This is then used to determine the effective communication area, so that the final first target area can have dynamic changing characteristics to meet the communication range requirements of the dynamically changing communication equipment.

[0078] Please see Figure 2 After steps S110-S130, considering the dynamic nature of network coverage, the steps to achieve the first target area include the following:

[0079] S210: Obtain multiple boundary parameters of the network coverage area, and determine the central parameter of the network coverage area based on these boundary parameters. The boundary parameters mainly refer to the boundary coordinate points of the network coverage area. These boundary coordinate points can characterize the points of interest or feature points of the shape contour of the obtained network coverage area. For example, when the contour formed by the network coverage area has corner points, the coordinates of these corner points are used as boundary parameters; similarly, when the contour of the network coverage area covers geographically abruptly changed locations, the coordinates of these locations can also be used as boundary parameters; furthermore, when the boundary parameters determined in the above manner are few, intermediate boundary parameter points can be added between the boundary parameters by dividing the area into segments, thereby more reasonably determining multiple reference boundary parameter data. The obtained boundary parameter data is centered by selecting a center point. This can be done using methods such as the orthocentric method (selecting as many boundary parameters as possible and using these parameters to determine a center point that has an almost uniform distance from all boundary parameters), or connecting all diagonally opposite boundary parameters to form a polygonal closed region, selecting the center point of this closed region as the centroid parameter; or using the ray method (determining a ray between every two boundary parameters and selecting the point where the rays intersect most frequently as the center parameter). Of course, the above only illustrates some methods for determining the center parameter from boundary parameters; those skilled in the art can choose other methods without creative effort, and no restrictions are placed here.

[0080] After determining the center parameter and all boundary parameters, proceed to step S220: Obtain the Euclidean distance between each boundary parameter and the center parameter, and calculate and obtain the mean value based on all obtained Euclidean distances. This means determining the Euclidean distances between all boundary parameters and the center parameter, averaging all Euclidean distance data, and using the average value as a reference before proceeding to step S230.

[0081] S230: Multiple boundary target regions are divided using a single boundary parameter as an arc point and the mean value as the radius. This means that the arc surface region is determined using the coordinates of each boundary parameter as the centroid and the mean value as the radius. This arc surface region refers to a portion of the area covered by concentric circles, i.e., the boundary target region. The multiple boundary target regions are then subjected to compensation transformation to determine the central target region. All boundary target regions and all central target regions together form multiple first target regions. After transforming the multiple boundary target regions, an enclosed annular contour pattern can be formed. The central target region is then determined based on the center of this annular contour. The transformation process can be at least one of smoothing, offsetting, or rotating the boundary target regions.

[0082] The technical solution obtained through the above steps takes into account the inherently changing nature of network coverage. Regardless of whether the network coverage boundary dynamically changes, the boundary target area and the central target area can be determined in real time using the above method. The reason for dividing the area into boundary target areas and central target areas is that, in actual mining operations, the central target area is often characterized by low mobility or low communication bandwidth requirements but stable and continuous communication. Therefore, in determining the central target area, it should be minimized from being too close to or near the outer contour of the boundary target area, thus serving as the communication center at the center. Of course, the central target area can be one or more, depending on the needs of the actual scenario. It can be determined based on the annular contour pattern enclosed by multiple boundary target areas, especially when the central hole of the annular hole is an elliptical hole or other holes with a high degree of irregularity. In addition, in some implementation scenarios, if the mining area will not change in a short period of time or the original exploration and mining range overlaps with the target exploration and mining range, the above steps S210-S230 can also be used to determine the boundary target area and the central target area. All the boundary target areas and all the central target areas are spliced ​​together to form the corresponding first target area, so as to avoid the occurrence of splicing dead corners (uncovered areas) as much as possible. It is also permissible for the boundary target areas to overlap with each other, the central target areas to overlap with each other, and the boundary target areas and the central target areas to overlap with each other.

[0083] In the above implementation, multiple boundary target regions are compensated and transformed to determine the central target region. This embodiment is implemented using the following steps, please refer to [link to relevant documentation]. Figure 4 :

[0084] S231: Based on concentricity, multiple boundary target areas are rotated in a compensatory manner to form a boundary enclosure area. Concentricity means that the centers of all boundary target areas lie on the same arc segment. If the deviation is too large or too dispersed, this arc segment needs to be determined in advance. The goal is to achieve concentricity by minimizing the offset of the centers of as many boundary target areas as possible. The main purpose of these steps is to correct or compensate for the deviation of multiple boundary target areas, arranging them as close to a circular array as possible to facilitate base station selection. It should be noted that this circular array does not necessarily need to be a standard circular array; any arrangement that facilitates the placement of communication base stations with a specified coverage radius is acceptable. The aim is to rationally plan the distribution and number of communication base stations, reducing the possibility of unreasonable coverage.

[0085] After determining all transformed boundary target regions, these regions can be stitched together to form a boundary enclosure region, leading to step S232: marking the central blank area of ​​the boundary enclosure region. For example, in a standard annular region, the central blank area is the circular area containing the inner hole; in an elliptical annular region, the central blank area is the elliptical area containing the inner hole. The central blank area is then analyzed and compared with the spatial range defined by the center parameter and the mean value result to obtain the first analysis result, indicating that the central blank area may have a relatively large size coverage. At this point, it is necessary to determine a reasonable distribution of the number of central target regions. A benchmark reference standard needs to be determined, using the space defined by the center parameter and the mean value result as the benchmark reference standard. Specifically, the circular coverage area drawn with the coordinates of the center parameter as the center and the mean value result as the radius is this benchmark reference standard. By comparing the coverage area with the central blank range using this benchmark reference standard, the first analysis result is obtained, and the process proceeds to step S233: the distribution of the central target area is determined based on the first analysis result. Here, the distribution mainly refers to the distribution location and the number of selections. For example, when the central blank range is two to three times the benchmark reference standard, two central target areas can be selected for distribution. The two central target areas can appropriately reduce the overlapping areas and fill the entire central blank range as much as possible.

[0086] Through steps S230-S233, the area is designed and considered in a way that is as standard as possible based on the relatively irregular outline of the mining area. On the one hand, it aims to effectively cover all communication needs. On the other hand, it aims to reduce the occurrence of unreasonable overlapping areas while meeting the former requirement. Furthermore, it aims to facilitate the selection of communication base stations with relatively uniform coverage areas, thereby facilitating actual material procurement and on-site construction.

[0087] To address the potential for blind spots in the target boundary area due to changes in the mining scope after its definition, please refer to the following guidelines again. Figure 4 After step S230 divides multiple boundary target regions using a single boundary parameter as an arc point and the mean value as the radius, it also includes the following steps:

[0088] S234: Obtain the set of distributions of all Euclidean distances and mean values, and integrate the subset of distributions of differences that meet the first preset threshold into the second analysis result. This means that when calculating the Euclidean distance between each boundary parameter and the central parameter, and calculating and obtaining the mean value based on all obtained Euclidean distances, the difference values ​​between all Euclidean distances and the mean value are obtained. All difference values ​​are organized into a set of distributions of difference values. From this set, Euclidean distances with larger or more abnormal difference values ​​are selected to identify and determine the boundary parameter. This boundary parameter belongs to the boundary parameter contained in the extended area after dynamic mining. This boundary parameter has reference value for local dynamic adjustment. These boundary parameters are integrated into the second analysis result, thus proceeding to step S234: Adjusting the distribution of the boundary target area formed by the corresponding boundary parameters based on the second analysis result. Through steps S234-S235, not only is the purpose of dynamic adjustment achieved, but the distribution of the boundary target area can also be updated cyclically during this dynamic adjustment, forming a recursive loop pattern. Finally, combined with the characteristics of dynamic mining in the mining area, a more reasonable division of the first target area is achieved.

[0089] The above steps considered the characteristics of dynamic mining and range changes. Next, we will further consider the characteristics of communication objects within the divided areas. Please refer to [link / reference needed]. Figure 5 In each primary target area, which does not contain different communication objects, the main communication characteristics to consider include: data transmission type, object movement range, data communication latency, and bandwidth. Data transmission type refers to the form of the data signal, such as voice, text, image, and video. Object movement range refers to the distance traveled, such as 0-5m, 5-50m, 50-2000m, and over 2000m. Data communication latency refers to the required delay in milliseconds, such as 0-10ms, 10-20ms, 20-40ms, and over 40ms. Bandwidth refers to the required communication speed, such as 5-10Mbps, 10-15Mbps, 15-20Mbps, 20-30Mbps, and over 30Mbps.

[0090] After determining the characteristics of the main communication objects mentioned above, step S300: analyzing the characteristics of the communication objects contained in each target area to obtain multiple characteristic distribution results includes the following steps:

[0091] S310: In each first target area, all communication objects are categorized according to the same characteristic to obtain multiple characteristic classification sets. This step allows for the classification and extraction of characteristics of all communication objects in each first target area. For example, communication characteristics belonging to data transmission type are extracted one by one; communication characteristics belonging to object movement range are extracted one by one; or communication characteristics of data communication delay or bandwidth rate are extracted one by one. At this time, all extracted communication characteristics can be organized into different categories and different sub-items under each category. Taking each category (containing only a single sub-item) as a characteristic classification set, multiple characteristic classification sets can be obtained, thus proceeding to step S230: Calculate the proportion and consideration priority of each characteristic classification set, generate characteristic correlation coefficients, and extract the characteristic correlation coefficients that meet the second preset threshold as the characteristic distribution result. Step S230 involves breaking down and statistically analyzing different communication objects into their smallest units (sub-items) of communication characteristics. This yields the percentage (probability of occurrence or proportion) of each category (containing only a single sub-item) and its consideration priority (weight). A comprehensive calculation is then performed to obtain the characteristic correlation coefficient. For example, if the percentage of data communication latency of 10-20ms is 19%, its consideration weight is 0.8, and its characteristic correlation coefficient could be 15.2 (19*0.8). Then, the characteristic correlation coefficient that meets the second preset threshold is used as the characteristic distribution result.

[0092] Through steps S310-S320, the communication needs of the communication objects can be comprehensively considered, and these needs can be broken down into statistically significant sub-elements. This serves as the basis for roughly describing the concentrated requirements of all communication objects in the first target area. Integrating all the obtained characteristic distribution results into a characteristic distribution matrix diagram or characteristic distribution matrix table for matching communication base stations is more reasonable. In the embodiment described above, step S400 may specifically adopt the following technical solution; please refer to [link / reference]. Figure 6 The process of determining a communication base station matching strategy based on each characteristic distribution matrix and then labeling the matched communication base stations includes the following steps:

[0093] S410: Determine the distance correlation between the characteristic distribution results in the characteristic distribution matrix, obtain multiple distance-correlated distribution results, and select the distance-correlated distribution results that meet the third preset threshold as the reference basic quantity. Through this step, since each characteristic distribution matrix contains multiple characteristic distribution results, the distance correlation of these characteristic distribution results can be calculated using the numerical representation method described above. This distance correlation calculation is mainly used to describe the distance between each characteristic distribution result and other characteristic distribution results, thereby determining the discrete distribution of each characteristic distribution result. Characteristic distribution results with higher discrete values ​​(compared to the third preset threshold) are temporarily eliminated, and characteristic distribution results with higher concentration are selected as the reference basic quantity. This is more conducive to the selection of communication base stations, ensuring that matching is met without excessively increasing other requirements for communication base stations, especially in cases where the same communication base station cannot easily meet all communication needs.

[0094] After obtaining the aforementioned reference basic quantities, proceed to step S420: Select the type and distribution location of communication base stations based on the reference basic quantities to determine the communication base station matching strategy. This step indicates that, given the determined reference basic quantities, the communication demand is highly concentrated. The smallest unit (sub-item) of all communication characteristics mapped by these reference basic quantities is used as the premise for determining the communication base station matching strategy. The matching strategy considers the type and distribution location of the communication base stations, which will not be elaborated upon here. Next, label the selected communication base stations, i.e., step S430: Extract the reference basic quantities belonging to the matched communication base stations again, decompose these reference basic quantities into multiple corresponding characteristic distribution results, and use each as its attribute label. These characteristic distribution results are statistically derived from the smallest unit (sub-item) of the communication characteristics. All smallest units (sub-items) belonging to this characteristic distribution result can be used as attribute labels for labeling, thereby enabling subsequent correlation measurement processing.

[0095] In actual operation, since the second preset threshold is initially determined by the user, there may be errors or non-standard selection under certain circumstances. This leads to the premature removal of some characteristic correlation coefficients that originally had a high proportion but relatively low weight. The characteristic distribution results corresponding to these correlation coefficients are more likely to match other characteristic distribution results in terms of actual communication demand satisfaction, thus facilitating the matching and selection of communication base stations. Therefore, to adapt to the above situation, the screening method based on the second preset threshold is modified and compensated to select attribute tags with higher concentration and easier matching. Specifically, after extracting the characteristic correlation coefficients that meet the second preset threshold as the characteristic distribution results, the following steps are also included: calculating the difference between each characteristic correlation coefficient that does not meet the second preset threshold requirement and the second preset threshold; arranging all differences in ascending order of absolute value to generate a difference distribution sequence; determining the mean scalar of all distance-related distribution results, obtaining the span between the mean scalar and the third preset threshold; extracting the characteristic correlation coefficients corresponding to the difference distribution sequence according to this span as the step size distance, and compensating as the characteristic distribution result. Through the above steps, the correlation coefficients of characteristics that fail to meet the second preset threshold requirement can be taken as compensation objects to be considered. Then, the correlation coefficients of the corresponding length are selected as compensation based on the span between the mean scalar and the third preset threshold as the characteristic distribution result. This recursive loop is implemented until all correlations or concentrations meet the requirements and convergence is achieved, so as to make it easier to match other characteristic distribution results with a better degree of communication requirement satisfaction.

[0096] The above steps allow us to extract the required attribute tags. However, these tags need further processing to facilitate the selection of communication base stations. Specifically, the following steps are performed in step S500. Please refer to [link / reference]. Figure 7 The process of performing correlation measurement on all attribute labels of the communication base station to obtain the indication output includes the following steps:

[0097] S510: Extract key information from each attribute tag, generate node information clusters, and classify the node information clusters to obtain multiple classification sets. This step splits and classifies attribute tags to make the data operable. For example, the key information for a broadband speed of 5-10Mbps is "broadband, 5-10". This information can be converted through data recognition, and by extracting and matching each attribute tag, multiple classification sets can be obtained. Then, proceed to step S520: Extract the classification sets that meet the preset requirements and merge them into the indication output result. That is, after obtaining multiple classification sets, their classification method is based on the rule that it is easier to operate through a single or specified power supply mode on the same communication base station. That is, the classification set is extracted in the way that it is easiest for the classification set to be compatible with other classification sets in terms of power supply. The extraction results are merged into the indication output result to guide the selection of power supply mode.

[0098] This embodiment also provides an open-pit mine 5G base station hybrid power supply system 700, please refer to [link / reference]. Figure 8 The modular schematic diagram of the power supply system 700 is mainly used to divide the power supply system 700 into functional modules according to the embodiments of the above method. For example, it can be divided into individual functional modules, or two or more functions can be integrated into one processing module. The integrated modules can be implemented in hardware or in software functional modules. It should be noted that the module division in this invention is illustrative and only represents one logical functional division; in actual implementation, there may be other division methods. For example, in the case of dividing each functional module according to its corresponding function, Figure 8 The diagram shown is only a schematic of a system / device, in which the power supply system 700 may include a first determining unit 710, a first analyzing unit 720, a first marking unit 730, a first calculating unit 740, and a first strategy unit 750. The functions of each unit module are described below.

[0099] The first determining unit 710 is used to determine the network coverage area of ​​the mining area and to divide the effective communication area based on the network coverage area to obtain multiple first target areas;

[0100] The first analysis unit 720 is used to analyze the characteristics of the communication objects contained in each of the first target regions, obtain multiple characteristic distribution results, and generate a characteristic distribution matrix based on the multiple characteristic distribution results;

[0101] The first labeling unit 730 is used to determine a communication base station matching strategy based on each of the feature distribution matrix diagrams, and to perform labeling processing on the multiple matched communication base stations respectively. The labeling processing refers to analyzing the attributes of the communication base stations to obtain multiple attribute labels.

[0102] The first calculation unit 740 is used to extract the attribute tags of each of the communication base stations, perform correlation measurement processing on all the attribute tags of the communication base station, and obtain an indication output result;

[0103] The first strategy unit 750 is used to select the power supply mode of the base station based on the indication output result, wherein the power supply mode includes a fuel power supply mode and / or an electric storage power supply mode.

[0104] In a possible implementation, the first determining unit 710 is further configured to: obtain multiple boundary parameters of the network coverage area; determine the center parameter of the network coverage area based on the multiple boundary parameters; obtain the Euclidean distance between each boundary parameter and the center parameter; calculate and obtain a mean value result based on all the obtained Euclidean distances; divide multiple boundary target regions with a single boundary parameter as an arc point and the mean value result as a radius; perform compensation transformation processing on the multiple boundary target regions to determine the center target region, wherein all the boundary target regions and all the center target regions together form multiple first target regions.

[0105] In a possible implementation, the power supply system 700 further includes a second determining unit, which is used to collect a resource coverage distribution information map of the mining area, and determine the original exploration and mining range and the target exploration and mining range based on the resource coverage distribution information map; calculate the distribution of the difference between the original exploration and mining range and the target exploration and mining range, and establish a dynamic mining plan table; update the work area range in real time based on the dynamic mining plan table, and determine the network coverage range of the mining area according to the work area range.

[0106] In a possible implementation, the first determining unit 710 is further configured to: perform a compensatory rotation on the plurality of boundary target regions based on concentricity to form a boundary enclosure region; mark the central blank range of the boundary enclosure region; analyze and compare the central blank range with the spatial range divided by the center parameter and the mean value result to obtain a first analysis result; and determine the distribution of the central target region based on the first analysis result.

[0107] In a possible implementation, the first determining unit 710 is further configured to: obtain a set of distributions of differences between all the Euclidean distances and the mean value results, integrate a subset of the distributions of differences that satisfy a first preset threshold into a second analysis result; and adjust the distribution of the boundary target region formed by the corresponding boundary parameters based on the second analysis result.

[0108] In a possible implementation, the first analysis unit 720 is further configured to: classify each communication object in each first target region according to the same characteristic to obtain multiple characteristic classification sets; calculate the proportion and consideration priority of each characteristic classification set, generate characteristic correlation coefficients, and extract characteristic correlation coefficients that satisfy a second preset threshold as the characteristic distribution result.

[0109] In a possible implementation, the first labeling unit 730 is further configured to: determine the distance correlation between the characteristic distribution results in the characteristic distribution matrix, obtain multiple distance-related distribution results, select the distance-related distribution results that satisfy a third preset threshold as a reference basic quantity; select the type and distribution location of the communication base station based on the reference basic quantity, thereby determining the communication base station matching strategy; extract the reference basic quantity belonging to the communication base station again for the matched communication base station, and decompose the reference basic quantity into multiple corresponding characteristic distribution results as their attribute labels respectively.

[0110] In a possible implementation, the first labeling unit 730 is further configured to: calculate the difference between each characteristic correlation coefficient that does not meet the second preset threshold requirement and the second preset threshold, and arrange all the differences in ascending order of absolute value to generate a difference distribution sequence; determine the mean scalar of all the distance correlation distribution results, and obtain the span between the mean scalar and the third preset threshold; extract the characteristic correlation coefficient corresponding to the difference distribution sequence according to the span as the step distance, and compensate as the characteristic distribution result.

[0111] In a possible implementation, the first calculation unit 740 is further configured to: extract key information of each attribute tag, generate node information clusters, and perform category classification processing on the node information clusters to obtain multiple classification sets; extract the classification sets that meet preset requirements, and merge them into the indication output result. It should be noted that the content implemented by each functional unit module is described in the method embodiment, and will not be repeated here.

[0112] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, optical fiber, DSL power supply line for 5G base stations in open-pit mines) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0113] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0114] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0115] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0116] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims of this application and their equivalents, this application also intends to include these modifications and variations.

Claims

1. A method for hybrid power supply of oil and electricity for 5G base stations in open-pit mines, characterized in that, The method includes the following steps: The network coverage area of ​​the mining area is determined, and the effective communication area is divided based on the network coverage area to obtain multiple first target areas. The effective communication area refers to the area that meets the communication requirements of the specified area. Analyze the characteristics of the communication objects contained in each of the first target regions to obtain multiple characteristic distribution results, and generate a characteristic distribution matrix based on the multiple characteristic distribution results; Based on each of the characteristic distribution matrix diagrams, a communication base station matching strategy is determined, and the matched communication base stations are labeled. The labeling process refers to analyzing the attributes of the communication base stations to obtain multiple attribute labels. Extract the attribute tags of each communication base station, perform correlation measurement on all the attribute tags of the communication base station, and obtain the indication output result; The power supply mode of the base station is selected based on the indicated output result, wherein the power supply mode includes fuel power supply mode and / or battery power supply mode; The step of dividing the effective communication area based on the network coverage to obtain multiple first target areas includes the following steps: obtaining multiple boundary parameters of the network coverage; determining the center parameter of the network coverage based on the multiple boundary parameters; obtaining the Euclidean distance between each boundary parameter and the center parameter; calculating and obtaining a mean value based on all the obtained Euclidean distances; dividing multiple boundary target areas with a single boundary parameter as an arc point and the mean value as a radius; performing compensation transformation on the multiple boundary target areas to determine the center target area; wherein all the boundary target areas and all the center target areas together form multiple first target areas.

2. The method for hybrid power supply of oil and electricity for 5G base stations in open-pit mines according to claim 1, characterized in that, Before determining the network coverage area of ​​the mining area, the following steps are also included: Collect a resource coverage distribution information map of the mining area, and determine the original exploration and mining scope and the target exploration and mining scope based on the resource coverage distribution information map of the mining area; Calculate the distribution of the difference between the original exploration and mining area and the target exploration and mining area, and establish a dynamic mining plan table; The operational area is updated in real time based on the dynamic mining plan, and the network coverage of the mining area is determined according to the operational area.

3. The method for hybrid power supply of 5G base stations in open-pit mines according to claim 2, characterized in that, The step of performing compensation transformation on multiple boundary target regions to determine the central target region includes the following steps: Based on concentricity, multiple boundary target regions are subjected to compensated rotation to form a boundary enclosed region; the central blank range of the boundary enclosed region is marked, and the central blank range is analyzed and compared with the spatial range divided by the center parameter and the mean value result to obtain a first analysis result; the distribution of the central target region is determined based on the first analysis result.

4. The method for hybrid power supply of 5G base stations in open-pit mines according to claim 3, characterized in that, After dividing the multiple boundary target regions using a single boundary parameter as an arc point and the mean value as a radius, the following steps are also included: Obtain the set of differences between all Euclidean distances and the mean value results, and integrate the subset of differences that satisfy the first preset threshold into the second analysis result; The distribution of the boundary target region formed by the corresponding boundary parameters is adjusted based on the second analysis result.

5. The method for hybrid power supply of oil and electricity for 5G base stations in open-pit mines according to claim 1, characterized in that, The characteristics of the communication object include: data transmission type, object movement range, data communication latency, and bandwidth rate; The analysis of the characteristics of the communication objects contained in each of the first target regions to obtain multiple characteristic distribution results includes the following steps: In each of the first target regions, the communication objects are categorized according to the same characteristic to obtain multiple characteristic categorization sets; Calculate the proportion and priority of each of the aforementioned feature classification sets, generate feature correlation coefficients, and extract the feature correlation coefficients that satisfy the second preset threshold as the feature distribution results.

6. The method for hybrid power supply of oil and electricity for 5G base stations in open-pit mines according to claim 5, characterized in that, The step of determining the communication base station matching strategy based on each of the characteristic distribution matrix diagrams and labeling the matched communication base stations includes the following steps: Determine the distance correlation between the characteristic distribution results in the characteristic distribution matrix diagram, obtain multiple distance correlation distribution results, and select the distance correlation distribution result that satisfies the third preset threshold as the reference basic quantity; Based on the reference basic quantities, the type and distribution location of the communication base stations are selected, thereby determining the communication base station matching strategy; For the matched communication base station, extract the reference basic quantity belonging to the communication base station again, and decompose the reference basic quantity into multiple corresponding characteristic distribution results as their attribute labels.

7. The method for hybrid power supply of oil and electricity for 5G base stations in open-pit mines according to claim 6, characterized in that, After extracting the feature correlation coefficients that satisfy the second preset threshold as the feature distribution result, the following steps are also included: Calculate the difference between the correlation coefficient of each characteristic that does not meet the second preset threshold requirement and the second preset threshold, and arrange all the differences in ascending order of absolute value to generate a difference distribution sequence; Determine the mean scalar of all the distance-related distribution results, and obtain the span between the mean scalar and the third preset threshold; The characteristic correlation coefficients corresponding to the difference distribution sequence are extracted according to the span as the step size distance, and the compensation is used as the characteristic distribution result.

8. The method for hybrid power supply of oil and electricity for 5G base stations in open-pit mines according to claim 1 or 7, characterized in that, The process of performing correlation measurement on all attribute tags of the communication base station to obtain the indication output result includes the following steps: Extract key information from each attribute tag, generate node information clusters, and perform category classification processing on the node information clusters to obtain multiple classification sets; Extract the classification sets that meet the preset requirements and merge them into the indicated output result.

9. A hybrid power supply system for 5G base stations in open-pit mines, characterized in that, include: The first determining unit is used to determine the network coverage area of ​​the mining area and to divide the effective communication area based on the network coverage area to obtain multiple first target areas; The first analysis unit is used to analyze the characteristics of the communication objects contained in each of the first target regions, obtain multiple characteristic distribution results, and generate a characteristic distribution matrix based on the multiple characteristic distribution results; The first labeling unit is used to determine the communication base station matching strategy based on each of the characteristic distribution matrix diagrams, and to label the matched communication base stations respectively. The labeling process refers to analyzing the attributes of the communication base stations to obtain multiple attribute labels. The first calculation unit is used to extract the attribute tags of each of the communication base stations, perform correlation measurement processing on all the attribute tags of the communication base station, and obtain an indication output result; The first strategy unit is used to select the power supply mode of the base station based on the indication output result, wherein the power supply mode includes fuel power supply mode and / or battery power supply mode. The first determining unit is further configured to obtain multiple boundary parameters of the network coverage area, determine the center parameter of the network coverage area based on the multiple boundary parameters; obtain the Euclidean distance between each boundary parameter and the center parameter, calculate and obtain a mean value based on all the obtained Euclidean distances; divide multiple boundary target regions with a single boundary parameter as an arc point and the mean value as a radius, perform compensation transformation processing on the multiple boundary target regions, and determine the center target region, wherein all the boundary target regions and all the center target regions together form multiple first target regions.

Images