Unmanned aerial vehicle low-altitude guarantee measurement method and system based on precise positioning

Abstract

The invention discloses an unmanned aerial vehicle low-altitude guarantee measurement method and system based on precise positioning, and relates to the technical field of unmanned aerial vehicle measurement, and the method comprises the steps: collecting low-altitude environment basic data, and setting an inspection node and an unmanned aerial vehicle cabin after analysis; collecting inspection node time change data, and determining an inspection time node and an inspection road section area; analyzing time change data of an inspection road section area, and planning an inspection path; and setting a speed dynamic change scheme of each inspection road section area according to the inspection path. The system comprises an inspection node setting module, an inspection road section setting module, an inspection path planning module, an inspection speed setting module and the like. Through comprehensive analysis of multi-dimensional data of the low-altitude environment, the inspection path and speed of the unmanned aerial vehicle are accurately planned, the measurement efficiency and accuracy are effectively improved, the risks of low-altitude signals, obstacles, privacy and the like are reduced, and the stability and safety of low-altitude measurement operation of the unmanned aerial vehicle are guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of UAV measurement technology, and in particular to a UAV low-altitude support measurement method and system based on precise positioning. Background Art

[0002] In many areas of modern society, such as urban planning, environmental monitoring, and infrastructure inspection, drone-based low-altitude measurement plays an increasingly important role. Drones can quickly and efficiently acquire various data in low-altitude areas, so a drone-based low-altitude measurement method and system based on precise positioning is needed.

[0003] Existing technologies, such as the invention patent application with announcement number CN118730055A, disclose a UAV surveying and mapping system based on deep learning; it includes: a UAV surveying and mapping terminal, in which the UAV surveying and mapping terminal has a built-in demand analysis module and a surveying and mapping optimization module; by real-time monitoring and comprehensive analysis of the data volume and transmission performance in the UAV surveying and mapping process, it can automatically generate optimization instructions, thereby improving the stability of data acquisition and the performance of network transmission, and providing effective support for subsequent surveying and mapping optimization; through reasonable priority sorting and transmission strategies, it improves the efficiency and reliability of data transmission, and optimizes the utilization of system resources; by quantitatively analyzing the degree of repeated mapping of each section in the flight path to determine the optimal degree of repeated mapping of each section, and accordingly optimize each section; it realizes dynamic adjustment of the UAV's flight path, avoids repeated mapping to the greatest extent, reduces repeated data transmission, and improves the effective collection and effective transmission of surveying and mapping data.

[0004] The above scheme has the following technical problems: 1. The above scheme is mainly based on a deep learning UAV surveying and mapping system, which mainly analyzes data processing and path optimization in the surveying and mapping process, but does not have the targetedness in the comprehensive guarantee and measurement of low-altitude environments. It does not take into account the risks of flight obstacles and privacy data in low-altitude environments. There may be limitations in its application in complex low-altitude environments, which reduces safety during flight.

[0005] 2. The above scheme mainly focuses on the overlap of surveying and mapping areas in flight path optimization. Although it adopts more complex methods such as genetic algorithms, it only considers path optimization from a single perspective such as overlap value, which is relatively one-sided. It does not take into account the time-varying data factors of inspection nodes. The data value and privacy risks of each inspection node will change over time. The above scheme cannot meet the time node requirements of each path node in the flight path, reducing the effectiveness of data collection and safety during the flight. Summary of the Invention

[0006] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide a UAV low-altitude support measurement method and system based on precise positioning.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a UAV low-altitude support measurement method based on precise positioning, comprising the following steps: Step 1, patrol node setting: Collect low-altitude environmental basic data, analyze the low-altitude environmental basic data, set each patrol node according to the analysis results, and then set each UAV cabin according to the low-altitude environmental basic data of each patrol node.

[0008] Step 2: Inspection section setting: collect time variation data of each inspection node, analyze the time variation data of each inspection node, set the inspection time node of each inspection node according to the analysis results, and then set the inspection section area.

[0009] Step 3: Inspection route planning: Collect time-varying data of each inspection section area, analyze the time-varying data of each inspection section area, and set the inspection route according to the analysis results.

[0010] Step 4: Inspection speed setting: According to the inspection route, collect the drone speed, and then set the speed dynamic change plan for each inspection section.

[0011] Preferably, the inspection time nodes of each inspection node are set, and the specific setting process is as follows: obtain the standard inspection stability index interval from the database, record the time node whose inspection stability index belongs to the standard inspection stability index interval as the standard time node, record the time node whose inspection stability index is greater than the upper limit of the standard inspection stability index interval as the high stability time node, and record the time node whose inspection stability index is less than the lower limit of the standard inspection stability index interval as the low stability time node, so as to obtain the high stability time nodes, standard time nodes and low stability time nodes within each inspection node cycle.

[0012] The measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each time node within each inspection node cycle are collected.

[0013] If the number of high-stable time nodes of a patrol node is one, the high-stable time node is recorded as the patrol time node of the patrol node; if there is no high-stable time node for a patrol node and the number of standard-stable time nodes is one, the standard-stable time node is recorded as the patrol time node of the patrol node; if the number of high-stable time nodes for a patrol node is greater than one, the time node with the maximum measurement value index is recorded as the patrol time node of the patrol node; if there is no high-stable time node for a patrol node and the number of standard-stable time nodes is greater than one, the time node with the minimum low-altitude privacy risk index is recorded as the patrol time node of the patrol node; if there is only low-stable time node for a patrol node, the time node with the minimum low-altitude obstacle risk index is recorded as the patrol time node of the patrol node, so as to obtain the patrol time node of each patrol node.

[0014] On the other hand, the present invention provides a UAV low-altitude support measurement system based on precise positioning, including the following modules: a patrol node setting module, which is used to collect basic data of the low-altitude environment, analyze the basic data of the low-altitude environment, set each patrol node according to the analysis results, and then set each UAV cabin according to the low-altitude environment basic data of each patrol node.

[0015] The inspection section setting module is used to collect the time change data of each inspection node, analyze the time change data of each inspection node, set the inspection time node of each inspection node according to the analysis results, and then set the inspection section area.

[0016] The inspection route planning module is used to collect time-varying data of each inspection section area, analyze the time-varying data of each inspection section area, and set the inspection route according to the analysis results.

[0017] The inspection speed setting module is used to collect the drone speed according to the inspection path, and then set the dynamic speed change plan for each inspection section.

[0018] The beneficial effects of the present invention are: 1. The present invention collects basic data of the low-altitude environment, and sets inspection nodes and unmanned vehicle cabins after analysis; collects time change data of inspection nodes, determines inspection time nodes and inspection road sections; analyzes time change data of inspection road sections and plans inspection routes; sets speed dynamic change schemes for each inspection road section according to the inspection route. The present invention accurately plans the inspection route and speed of unmanned aerial vehicles through comprehensive analysis of multi-dimensional data of the low-altitude environment, effectively improves measurement efficiency and accuracy, reduces risks such as low-altitude signals, obstacles, and privacy, and ensures the stability and safety of unmanned aerial vehicle low-altitude measurement operations.

[0019] 2. The present invention fully considers the complexity of the low-altitude environment and incorporates a variety of data such as the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index, and low-altitude privacy risk index into the analysis. When setting up inspection nodes, standard measurement points and high-efficiency measurement points are reasonably divided according to the effective value assessment index of the measurement points; when setting up unmanned aerial vehicle cabins, the distance between the invalid measurement point and the end point of the area, the low-altitude signal risk index, and the low-altitude obstacle risk index are comprehensively calculated to calculate the charging compartment usage index and accurately select the site. In terms of time dimension, the inspection stability index is calculated using the trends of multiple indexes at each time node within each inspection node cycle, and the inspection time nodes are reasonably set, so that the drone inspection can better adapt to the complex and changeable low-altitude environment, reduce the risks of signal interference, obstacle collision, privacy leakage, etc., and enhance system reliability.

[0020] 3. The present invention's dynamic inspection speed adjustment scheme determines speed ranges based on the inspection effectiveness value assessment index of the inspection section and dynamically adjusts the drone's speed based on the inspection stability index. If the drone's speed exceeds the reasonable range or the stability index becomes abnormal, the speed is adjusted promptly to ensure that the drone can complete the measurement task at the optimal speed across different sections and time points. This ensures measurement accuracy while allowing for flexible adjustments based on actual conditions, improving task execution efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 The figure is a schematic flow chart of the steps for implementing the method of the present invention.

[0023] Figure 2 This is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0025] according to Figure 1As shown, the present invention provides a UAV low-altitude support measurement method based on precise positioning, comprising the following steps: Step 1, patrol node setting: collecting low-altitude environmental basic data, analyzing the low-altitude environmental basic data, setting each patrol node according to the analysis results, and then setting each UAV cabin according to the low-altitude environmental basic data of each patrol node.

[0026] In a specific embodiment, basic data of the low-altitude environment is collected, and the specific collection process is as follows: the basic data of the low-altitude environment includes the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each measurement point, and the picture of each measurement point is collected by a camera, and the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each measurement point are obtained by image recognition technology.

[0027] It should be noted that the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each standard picture are preset, and the feature vectors of each collected picture and each standard picture are obtained through image recognition technology. The feature vector of the picture includes but is not limited to the grayscale and color difference of each pixel in the picture. The feature vectors of each collected picture and each standard picture are substituted into the cosine similarity calculation formula to obtain the similarity between the collected picture and each standard picture. The measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of the standard picture with the maximum similarity are recorded as the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of the collected picture, so as to obtain the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each measurement point.

[0028] The measurement value index of the standard image is obtained by dividing the number of image pixels with the data to be measured by the total number of image pixels. The low-altitude signal risk index of the standard image is obtained by dividing the number of noise pixels in the standard image by the total number of image pixels. The low-altitude obstacle risk index of the standard image is obtained by dividing the number of obstacle pixels in the standard image by the total number of image pixels. The low-altitude privacy risk index of the standard image is obtained by dividing the number of image pixels with privacy data by the total number of image pixels.

[0029] The larger the measurement value index of a measurement point, the larger the amount of data that can be measured at the measurement point. The larger the low-altitude signal risk index of the measurement point, the worse the signal transmission stability at the measurement point. The larger the low-altitude obstacle risk index of the measurement point, the more low-altitude flight obstacles there are. The larger the low-altitude privacy risk index of the measurement point, the more privacy data is collected at the measurement point.

[0030] In a specific embodiment, the welding requirement data of each welding node of the truss is analyzed, and the specific analysis process is as follows: the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each measuring point are substituted into the inspection effective value assessment index calculation formula to obtain the effective value assessment index of each measuring point.

[0031] It should be noted that the calculation formula for the inspection effectiveness value assessment index is:

[0032]

[0033] Among them, α a is the effective value evaluation index of measurement point a, a is the number of each measurement point, the value of a is a positive integer, T 1a 、T 2a 、T 3a and T 4a where ε1 is the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of the measurement point a, respectively. T′1, T′2, T3′ and T4′ are the preset standard measurement value index, standard low-altitude signal risk index, standard low-altitude obstacle risk index and standard low-altitude privacy risk index, respectively. ε1, ε2, ε3 and ε4 are the preset measurement value index weight factor, low-altitude signal risk index weight factor, low-altitude obstacle risk index weight factor and low-altitude privacy risk index weight factor, respectively. ε1>0, ε2>0, ε3>0, ε4>0, ε1+ε2+ε3+ε4=1.

[0034] The standard parameters T1′, T′2, T3′, and T4′ are the measurement value index threshold, low-altitude signal risk index threshold, low-altitude obstacle risk index threshold, and low-altitude privacy risk index threshold of normal inspection points, respectively. When the measurement value index is greater than the threshold, it indicates that the amount of measurable data at the measurement point is large. When the low-altitude signal risk index is greater than the threshold, it indicates that the signal transmission is unstable. When the low-altitude obstacle risk index is greater than the threshold, it indicates that obstacles are likely to be encountered during flight. When the low-altitude privacy risk index is greater than the threshold, it indicates that a large amount of privacy data is collected during the collection process. The specific values ​​of the standard parameters are set by the staff, for example, T1′ is 0.56, T′2 is 0.36, T3′ is 0.347, and T4′ is 0.28. The setting process of the weight factor is set by the staff, and the specific values ​​are, for example, ε1 is 0.3, ε2 is 0.3, ε3 is 0.2, and ε4 is 0.2.

[0035] In a specific embodiment, the setting of each inspection node is specifically performed as follows: obtaining the effective value assessment index interval of the standard measurement point from the database; if the effective value assessment index of a certain measurement point belongs to the effective value assessment index interval of the standard measurement point, the measurement point is recorded as the standard measurement point, thereby obtaining each standard measurement point; if the effective value assessment index of a certain measurement point is greater than the upper limit of the effective value assessment index interval of the standard measurement point, the measurement point is recorded as an efficient measurement point, thereby obtaining each efficient measurement point.

[0036] The basic inspection path is set through the map model of the area. The starting point of the basic inspection path is used as the starting point of the first inspection area, and each standard distance is the inspection distance. The basic inspection path area is divided to obtain each type of first inspection area corresponding to each standard distance. The number of standard measurement points in each type of first inspection area is obtained by counting. The number of standard measurement points in each type of first inspection area is subtracted from the number of standard inspection measurement points to obtain the difference in the number of standard measurement points in each type of first inspection area. The standard distance corresponding to the minimum difference in the number of standard measurement points is recorded as the inspection distance of the first inspection area. In this way, the first inspection area is divided from the basic inspection path area. The end point of the first inspection area is used as the starting point of the second inspection area. According to the acquisition plan of the first inspection area, the second inspection area is obtained to obtain each inspection area.

[0037] If the number of efficient measurement points in a certain inspection area is greater than one, the efficient measurement point with the highest measurement value index is selected as the inspection node of the inspection area. If the number of efficient measurement points in a certain inspection area is equal to one, the efficient measurement point of the inspection area is recorded as the inspection node. If the number of efficient measurement points in a certain inspection area is zero, the inspection point with the minimum low-altitude privacy risk index is selected as the inspection node of the inspection area. Each inspection node is set in this way.

[0038] In a specific embodiment, the setting of each unmanned cabin is specifically carried out as follows: the number of standard inspection measurement points is used to obtain each inspection area, and the number of standard usage measurement points is set, and then the inspection basic path area is divided into each charging inspection area.

[0039] If the effective value evaluation index of a measurement point is less than the lower limit of the effective value evaluation index range of the standard measurement point, the measurement point is recorded as an invalid measurement point, thereby obtaining the invalid measurement points of each charging inspection area.

[0040] Through the map simulation area, the inspection area map is obtained, and the distance between each invalid measurement point in each charging inspection area and the end point of the corresponding area is obtained through image recognition technology. The distance between each invalid measurement point in each charging inspection area and the end point of the corresponding area, the low-altitude signal risk index and the low-altitude obstacle risk index are substituted into the charging warehouse utilization index calculation formula to obtain the charging warehouse utilization index of each invalid measurement point in each charging inspection area, and each unmanned cabin is set at the invalid measurement point position of the maximum charging warehouse utilization index in each charging inspection area.

[0041] It should be noted that a signal transmitter is set up in the drone cabin to improve the anti-electromagnetic interference effect of low-altitude drone flight and ensure the effectiveness of information transmission. The calculation formula of the charging compartment usage index is: Where γbg is the charging bin usage index of the invalid measurement point g in the charging inspection area b, b is the number of each charging inspection area, the value of b is a positive integer, g is the number of each invalid measurement point, the value of g is a positive integer, T 2bg 、T 3bg and L bg are the distance between the invalid measurement point g in the charging inspection area b and the end point of the corresponding area, the low-altitude signal risk index, and the low-altitude obstacle risk index, respectively. L′ is the preset standard distance.

[0042] L′ is set by the staff and is generally set to the average distance from the starting point to the midpoint of the inspection area, for example, L′ is 0.5.

[0043] Step 2: Inspection section setting: collect time variation data of each inspection node, analyze the time variation data of each inspection node, set the inspection time node of each inspection node according to the analysis results, and then set the inspection section area.

[0044] In a specific embodiment, the time-varying data of each inspection node is collected, and the specific collection process is as follows: the time-varying data of each inspection node includes the measurement value index trend index, low-altitude signal risk index trend index, low-altitude obstacle risk index trend index and low-altitude privacy risk index trend index of each time node within each inspection node cycle. Through the collection method of low-altitude environmental basic data, the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each time node within each inspection node cycle are collected.

[0045] The measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each time node in each inspection node cycle are plotted in the order of the time nodes in the cycle to obtain the measurement value index change graph, low-altitude signal risk index change graph, low-altitude obstacle risk index change graph and low-altitude privacy risk index change graph of each inspection node. The slope of the measurement value index curve, the slope of the low-altitude signal risk index curve, the slope of the low-altitude obstacle risk index curve and the slope of the low-altitude privacy risk index curve of each time node in each inspection node cycle are obtained through image recognition technology. The trend index corresponding to each curve slope is obtained from the database to obtain the measurement value index trend index, low-altitude signal risk index trend index, low-altitude obstacle risk index trend index and low-altitude privacy risk index trend index of each time node in each inspection node cycle.

[0046] In a specific embodiment, the time-varying data of each inspection node is analyzed, and the specific analysis process is as follows: the measurement value index trend index, low-altitude signal risk index trend index, low-altitude obstacle risk index trend index and low-altitude privacy risk index trend index of each time node within each inspection node cycle are substituted into the inspection stability index calculation formula to obtain the inspection stability index of each time node within each inspection node cycle.

[0047] It should be noted that the calculation formula for the inspection stability index is:

[0048] Among them, β cd is the inspection stability index of the d time node within the c inspection node cycle, c is the number of the inspection node, the value of c is a positive integer, d is the number of the time node, the value of d is a positive integer, e is a natural constant, f 1ab 、f 2ab 、f 3ab and f 4ab are the measurement value index trend index, low-altitude signal risk index trend index, low-altitude obstacle risk index trend index and low-altitude privacy risk index trend index of time node d within the inspection node c period, respectively; f1′, f′2, f3′ and f4′ are the preset standard measurement value index trend index, standard low-altitude signal risk index trend index, standard low-altitude obstacle risk index trend index and standard low-altitude privacy risk index trend index, respectively; φ1, φ2, φ3 and φ4 are the preset measurement value index trend index weight factor, low-altitude signal risk index trend index weight factor, low-altitude obstacle risk index trend index weight factor and low-altitude privacy risk index trend index weight factor, respectively; φ1>0, φ2>0, φ3>0, φ4>0, φ1+φ2+φ3+φ4=1.

[0049] The setting process of the standard parameters f1′, f′2, f′3 and f′4 is the same as that of the standard parameter T1′, and they are all set by the staff, for example, f1′ is 0.85, f′2 is 0.8, f′3 is 0.75 and f′4 is 0.9. The setting process of the weight factors φ1, φ2, φ3 and φ4 is the same as that of the weight factor ε1, and they are all set by the staff, for example, φ1 is 0.25, φ2 is 0.3, φ3 is 0.25 and φ4 is 0.3.

[0050] In a specific embodiment, the inspection time nodes of each inspection node are set, and the specific setting process is as follows: obtain the standard inspection stability index interval from the database, record the time node whose inspection stability index belongs to the standard inspection stability index interval as the standard time node, record the time node whose inspection stability index is greater than the upper limit of the standard inspection stability index interval as the high stability time node, and record the time node whose inspection stability index is less than the lower limit of the standard inspection stability index interval as the low stability time node, so as to obtain the high stability time nodes, standard time nodes and low stability time nodes within each inspection node cycle.

[0051] The measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each time node within each inspection node cycle are collected.

[0052] If the number of high-stable time nodes of a patrol node is one, the high-stable time node is recorded as the patrol time node of the patrol node; if there is no high-stable time node for a patrol node and the number of standard-stable time nodes is one, the standard-stable time node is recorded as the patrol time node of the patrol node; if the number of high-stable time nodes for a patrol node is greater than one, the time node with the maximum measurement value index is recorded as the patrol time node of the patrol node; if there is no high-stable time node for a patrol node and the number of standard-stable time nodes is greater than one, the time node with the minimum low-altitude privacy risk index is recorded as the patrol time node of the patrol node; if there is only low-stable time node for a patrol node, the time node with the minimum low-altitude obstacle risk index is recorded as the patrol time node of the patrol node, so as to obtain the patrol time node of each patrol node.

[0053] In a specific embodiment, the setting of each inspection section area is carried out as follows: if the inspection time node of a certain inspection node is adjacent to the inspection time node of an adjacent inspection node within a cycle, it indicates that the inspection node and the adjacent inspection node are in the same inspection section, and the inspection areas corresponding to the inspection nodes in the same inspection section area are summarized to obtain the inspection section areas.

[0054] Step 3: Inspection route planning: Collect time-varying data of each inspection section area, analyze the time-varying data of each inspection section area, and set the inspection route according to the analysis results.

[0055] In a specific embodiment, the time-varying data of each inspection section area is collected, and the specific collection process is as follows: according to the collection process of the time-varying data of each inspection node, the time-varying data of each inspection section area is collected.

[0056] In a specific embodiment, the inspection path is set up, and the specific setting process is as follows: according to the analysis method of the inspection time nodes of the inspection nodes, the inspection time nodes of each inspection section area are analyzed and obtained, according to the order of each time node within the cycle, each inspection section area is sorted to obtain the inspection order within the cycle of each inspection section area, and the measurement value index and low-altitude privacy risk index of the inspection time node of each inspection section area are collected, and the measurement value index and low-altitude privacy risk index of the inspection time node of each inspection section area are substituted into the patrol measurement index calculation formula to obtain the patrol measurement index of each inspection section area, and according to the patrol measurement index of each inspection section area and the patrol order position within the cycle, the basic inspection path is analyzed by genetic algorithm to obtain the patrol path, and the inspection path is set accordingly.

[0057] Step 4: Inspection speed setting: According to the inspection route, collect the drone speed, and then set the speed dynamic change plan for each inspection section.

[0058] In a specific embodiment, the speed dynamic change scheme for each inspection section area is set, and the specific setting process is as follows: the inspection speed corresponding to each inspection effective value evaluation index is obtained from the database, the minimum inspection speed corresponding to the inspection effective value evaluation index of each inspection node in each inspection section area is recorded as the lower limit of the inspection speed range, and the maximum inspection speed corresponding to the inspection effective value evaluation index of each inspection node in each inspection section area is recorded as the upper limit of the inspection speed range, thereby obtaining the inspection speed range of each inspection section area.

[0059] The inspection stability index of each inspection node in each inspection section area is calculated by weighted average to obtain the inspection stability index of each inspection section area.

[0060] It should be noted that the greater the time interval between the inspection time node of each inspection node and the inspection time node of the corresponding inspection section area within the cycle, the greater the weight factor of the inspection node in the weighted average price calculation process.

[0061] The dynamic speed change plan for each inspection section is as follows: when the speed of the UAV at a certain inspection node is less than the lower limit of the corresponding inspection speed range, the inspection speed of the UAV is increased to the lower limit of the inspection speed range; when the speed of the UAV at a certain inspection node is greater than the upper limit of the corresponding inspection speed range, the inspection speed of the UAV is increased to the upper limit of the inspection speed range; when the speed of the UAV at a certain inspection node belongs to the corresponding inspection speed range, if the inspection stability index of the inspection node is less than the lower limit of the standard inspection stability index range, the inspection speed of the UAV is reduced; if the inspection stability index of the inspection node is greater than the upper limit of the standard inspection stability index range, the inspection speed of the UAV is increased.

[0062] according to Figure 2 As shown, the present invention provides a UAV low-altitude support measurement system based on precise positioning, which includes the following modules: an inspection node setting module, an inspection section setting module, an inspection path planning module, an inspection speed setting module and a database.

[0063] The inspection section setting module is connected to the inspection node setting module and the inspection path planning module respectively, the inspection speed setting module is connected to the inspection path planning module, and the inspection node setting module, inspection section setting module, inspection path planning module, and inspection speed setting module are all connected to the database.

[0064] The inspection node setting module is used to collect basic data of the low-altitude environment, analyze the basic data of the low-altitude environment, set each inspection node according to the analysis results, and then set each drone warehouse according to the basic data of the low-altitude environment of each inspection node.

[0065] The inspection section setting module is used to collect the time change data of each inspection node, analyze the time change data of each inspection node, set the inspection time node of each inspection node according to the analysis results, and then set the inspection section area.

[0066] The inspection route planning module is used to collect time-varying data of each inspection section area, analyze the time-varying data of each inspection section area, and set the inspection route according to the analysis results.

[0067] The inspection speed setting module is used to collect the drone speed according to the inspection path, and then set the dynamic speed change plan for each inspection section.

[0068] The database is used to store the effective value evaluation index intervals of standard measurement points, the standard inspection stability index intervals, the trend index corresponding to the slope of each curve, and the inspection speed corresponding to the effective value evaluation index of each inspection.

[0069] The above content is merely an example and explanation of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. A method for low-altitude measurement of UAVs based on precise positioning, characterized in that: The steps include: Step 1: Inspection node setting: Collect basic data of low-altitude environment, analyze the basic data of low-altitude environment, set each inspection node according to the analysis results, and then set each unmanned cabin according to the basic data of low-altitude environment of each inspection node; Step 2: Inspection section setting: collect time variation data of each inspection node, analyze the time variation data of each inspection node, set the inspection time node of each inspection node according to the analysis results, and then set the inspection section area; Step 3: Inspection route planning: collect time-varying data of each inspection section, analyze the time-varying data of each inspection section, and set the inspection route based on the analysis results; Step 4: Inspection speed setting: According to the inspection route, collect the drone speed, and then set the speed dynamic change plan for each inspection section.

2. The method for low-altitude measurement of an unmanned aerial vehicle based on precise positioning according to claim 1 is characterized in that: The welding requirement data of each welding node of the truss is analyzed, and the specific analysis process is as follows: The basic data of low-altitude environment include the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each measurement point. The measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index of each measurement point are substituted into the calculation formula of the patrol effective value assessment index to obtain the effective value assessment index of each measurement point.

3. The method for low-altitude measurement of an unmanned aerial vehicle based on precise positioning according to claim 2, characterized in that: The specific setting process of setting each inspection node is as follows: Obtain the effective value evaluation index interval of the standard measurement points from the database. If the effective value evaluation index of a certain measurement point belongs to the effective value evaluation index interval of the standard measurement point, record the measurement point as the standard measurement point, thereby obtaining each standard measurement point. If the effective value evaluation index of a certain measurement point is greater than the upper limit of the effective value evaluation index interval of the standard measurement point, record the measurement point as the efficient measurement point, thereby obtaining each efficient measurement point. A basic inspection path is set through a map model of the area. The starting point of the basic inspection path is used as the starting point of the first inspection area, and each standard distance is used as the inspection distance. The basic inspection path area is divided to obtain each type of first inspection area corresponding to each standard distance. The number of standard measurement points in each type of first inspection area is obtained by counting. The number of standard measurement points in each type of first inspection area is subtracted from the number of standard inspection measurement points to obtain the difference in the number of standard measurement points in each type of first inspection area. The standard distance corresponding to the minimum difference in the number of standard measurement points is recorded as the inspection distance of the first inspection area. In this way, the first inspection area is divided from the basic inspection path area. The end point of the first inspection area is used as the starting point of the second inspection area. According to the acquisition plan of the first inspection area, the second inspection area is obtained, thereby obtaining each inspection area. If the number of efficient measurement points in a certain inspection area is greater than one, the efficient measurement point with the highest measurement value index is selected as the inspection node of the inspection area. If the number of efficient measurement points in a certain inspection area is equal to one, the efficient measurement point of the inspection area is recorded as the inspection node. If the number of efficient measurement points in a certain inspection area is zero, the inspection point with the minimum low-altitude privacy risk index is selected as the inspection node of the inspection area. Each inspection node is set in this way.

4. The method for low-altitude measurement of an unmanned aerial vehicle based on precise positioning according to claim 3 is characterized in that: The specific setting process of setting each unmanned aircraft cabin is as follows: By using the method of obtaining each inspection area through the number of standard inspection measurement points, the standard number of measurement points is set, and then the inspection basic path area is divided into each charging inspection area; If the effective value evaluation index of a certain measurement point is less than the lower limit of the effective value evaluation index range of the standard measurement point, the measurement point is recorded as an invalid measurement point, thereby obtaining the invalid measurement points of each charging inspection area; Through the map simulation area, the inspection area map is obtained, and the distance between each invalid measurement point in each charging inspection area and the end point of the corresponding area is obtained through image recognition technology. The distance between each invalid measurement point in each charging inspection area and the end point of the corresponding area, the low-altitude signal risk index and the low-altitude obstacle risk index are substituted into the charging warehouse utilization index calculation formula to obtain the charging warehouse utilization index of each invalid measurement point in each charging inspection area, and each unmanned cabin is set at the invalid measurement point position of the maximum charging warehouse utilization index in each charging inspection area.

5. The method for low-altitude measurement of an unmanned aerial vehicle based on precise positioning according to claim 1 is characterized in that: The time variation data of each inspection node is analyzed, and the specific analysis process is as follows: The time change data of each inspection node include the measurement value index trend index, low-altitude signal risk index trend index, low-altitude obstacle risk index trend index and low-altitude privacy risk index trend index of each time node in each inspection node cycle. The measurement value index trend index, low-altitude signal risk index trend index, low-altitude obstacle risk index trend index and low-altitude privacy risk index trend index of each time node in each inspection node cycle are substituted into the inspection stability index calculation formula to obtain the inspection stability index of each time node in each inspection node cycle.

6. The method for low-altitude measurement of an unmanned aerial vehicle based on precise positioning according to claim 5 is characterized in that: The specific setting process of setting the inspection time node of each inspection node is as follows: Obtain the standard inspection stability index interval from the database, record the time node whose inspection stability index belongs to the standard inspection stability index interval as the standard time node, record the time node whose inspection stability index is greater than the upper limit of the standard inspection stability index interval as the high stability time node, and record the time node whose inspection stability index is less than the lower limit of the standard inspection stability index interval as the low stability time node, thereby obtaining each high stability time node, each standard time node and low stability time node within each inspection node cycle; Collect the measurement value index, low-altitude signal risk index, low-altitude obstacle risk index and low-altitude privacy risk index at each time node within each inspection node cycle; If the number of high-stable time nodes of a patrol node is one, the high-stable time node is recorded as the patrol time node of the patrol node; if there is no high-stable time node for a patrol node and the number of standard-stable time nodes is one, the standard-stable time node is recorded as the patrol time node of the patrol node; if the number of high-stable time nodes for a patrol node is greater than one, the time node with the maximum measurement value index is recorded as the patrol time node of the patrol node; if there is no high-stable time node for a patrol node and the number of standard-stable time nodes is greater than one, the time node with the minimum low-altitude privacy risk index is recorded as the patrol time node of the patrol node; if there is only low-stable time node for a patrol node, the time node with the minimum low-altitude obstacle risk index is recorded as the patrol time node of the patrol node, so as to obtain the patrol time node of each patrol node.

7. The method for low-altitude measurement of an unmanned aerial vehicle based on precise positioning according to claim 6, characterized in that: The specific setting process for setting each inspection section area is as follows: If the inspection time node of a certain inspection node is adjacent to the inspection time node of an adjacent inspection node within a cycle, it indicates that the inspection node and the adjacent inspection node are in the same inspection section. The inspection areas corresponding to the inspection nodes in the same inspection section area are summarized to obtain the areas of each inspection section.

8. The method for low-altitude measurement of an unmanned aerial vehicle based on precise positioning according to claim 7 is characterized in that: The specific setting process of setting the inspection path is as follows: According to the analysis method of the inspection time nodes of the inspection nodes, the inspection time nodes of each inspection section area are analyzed and obtained. According to the order of each time node within the cycle, each inspection section area is sorted to obtain the inspection order of each inspection section area within the cycle. The measurement value index and low-altitude privacy risk index of the inspection time nodes of each inspection section area are collected. The measurement value index and low-altitude privacy risk index of the inspection time nodes of each inspection section area are substituted into the patrol measurement index calculation formula to obtain the patrol measurement index of each inspection section area. According to the patrol measurement index of each inspection section area and the inspection order position within the cycle, the basic inspection path is analyzed by genetic algorithm to obtain the patrol path, and the inspection path is set accordingly.

9. The method for low-altitude measurement of an unmanned aerial vehicle based on precise positioning according to claim 8, characterized in that: The specific setting process of setting the dynamic speed change plan for each inspection section area is as follows: Obtain the inspection speed corresponding to each inspection effective value evaluation index from the database, record the minimum inspection speed corresponding to the inspection effective value evaluation index of each inspection node in each inspection section area as the lower limit of the inspection speed interval, and record the maximum inspection speed corresponding to the inspection effective value evaluation index of each inspection node in each inspection section area as the upper limit of the inspection speed interval, so as to obtain the inspection speed interval of each inspection section area; The inspection stability index of each inspection node in each inspection section area is calculated by weighted average to obtain the inspection stability index of each inspection section area; The dynamic speed change plan for each inspection section is as follows: when the speed of the UAV at a certain inspection node is less than the lower limit of the corresponding inspection speed range, the inspection speed of the UAV is increased to the lower limit of the inspection speed range; when the speed of the UAV at a certain inspection node is greater than the upper limit of the corresponding inspection speed range, the inspection speed of the UAV is increased to the upper limit of the inspection speed range; when the speed of the UAV at a certain inspection node belongs to the corresponding inspection speed range, if the inspection stability index of the inspection node is less than the lower limit of the standard inspection stability index range, the inspection speed of the UAV is reduced; if the inspection stability index of the inspection node is greater than the upper limit of the standard inspection stability index range, the inspection speed of the UAV is increased.

10. A measurement system using the UAV low-altitude support measurement method based on precise positioning according to any one of claims 1 to 9, characterized in that: Includes the following modules: The inspection node setting module is used to collect basic data of the low-altitude environment, analyze the basic data of the low-altitude environment, set each inspection node according to the analysis results, and then set each unmanned cabin according to the basic data of the low-altitude environment of each inspection node; The inspection section setting module is used to collect the time variation data of each inspection node, analyze the time variation data of each inspection node, set the inspection time node of each inspection node according to the analysis results, and then set the inspection section area; Inspection route planning module, used to collect time-varying data of each inspection section area, analyze the time-varying data of each inspection section area, and set the inspection route according to the analysis results; The inspection speed setting module is used to collect the drone speed according to the inspection path, and then set the dynamic speed change plan for each inspection section.

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