Unmanned aerial vehicle collection method based on urban rail transit engineering monitoring

Abstract

The invention discloses an unmanned aerial vehicle collection method based on urban rail transit engineering monitoring, and relates to the technical field of unmanned aerial vehicle detection flight. The unmanned aerial vehicle acquisition method based on urban rail transit engineering monitoring comprises the following steps: S1, establishing a ground three-dimensional model by adopting an unmanned aerial vehicle radar scanning and oblique photogrammetry technology, comparing ground subsidence changes in different construction stages of rail transit construction, and verifying precision and reliability by comparing unmanned aerial vehicle data with traditional manual monitoring data; and S2, researching and determining the technical requirements of the data acquisition route and range of the unmanned aerial vehicle according to the deformation rule and range of the settlement area of different construction methods. According to the invention, an unmanned aerial vehicle collection mode is adopted, a large area can be covered in a short time, and the detection efficiency is greatly improved. And meanwhile, the unmanned aerial vehicle flies by adopting a fuzzy logic control algorithm, so that the unmanned aerial vehicle can flexibly fly in the urban rail transit, and the safety is higher.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicle (UAV) detection flight, and particularly relates to a UAV acquisition method based on urban rail transit engineering monitoring. Background Technique

[0002] UAV remote sensing technology is an application technology that can automatically, intelligently, and specifically obtain spatial remote sensing information such as land resources, natural environment, and earthquake-stricken areas, and complete remote sensing data processing, modeling, and application analysis. In recent years, with the rapid development of computer technology and communication technology, and the continuous emergence of various new sensors with digitalization, light weight, small size, and high detection accuracy, the performance of UAVs has been continuously improved, the application scope and application fields have been rapidly expanded, and UAV remote sensing technology has begun to be widely used in geological disaster monitoring, ground subsidence monitoring in mining areas, safety risk inspection of foundation pit construction, and inspection of subway protection areas.

[0003] However, when the UAV actually flies to collect data, the flight speed and stability of the UAV are easily affected by environmental factors. For example, in an urban environment with many high-rise buildings, the GPS signal will be refracted multiple times, resulting in positioning deviation or even confusion, increasing the risk of UAV out of control. In addition, radio signal interference in areas with high-rise building density will also affect the remote control signal of the UAV, shortening its safe remote control distance. Summary of the Invention

[0004] The purpose of the present invention is to provide a UAV acquisition method based on urban rail transit engineering monitoring to solve the problems raised in the above background technique.

[0005] To achieve the above invention purpose, the present invention adopts the following technical solutions:

[0006] The present invention provides a UAV acquisition method based on urban rail transit engineering monitoring, including the following steps:

[0007] S1. Use UAV radar scanning and oblique photogrammetry technology to establish a ground three-dimensional model, compare the ground settlement changes in different construction stages of rail transit construction, and verify the accuracy and reliability by comparing UAV data with traditional manual monitoring data;

[0008] S2. Study and determine the technical requirements for UAV data acquisition routes and ranges according to the deformation laws and ranges of settlement areas with different construction methods;

[0009] S3. Establish a data model based on UAV technology for collapse warning standards in rail transit engineering with an engineering example as the background.

[0010] As a preferred embodiment of the present invention, in S1, the data acquisition method using drone radar scanning and oblique photogrammetry technology is the elastic model method, and the K-value surface area ratio is used to estimate and calculate the settlement of the rail transit foundation.

[0011] Among them, it is assumed that the rail transit foundation is a brittle material. According to the principle of volume stability, when a load occurs on the rail transit foundation, the settlement amount s of the rail transit foundation can be expressed as:

[0012] s = K·q / F;

[0013] Where: s: the settlement amount of the rail transit foundation, m; K: the settlement coefficient, m / t; q: the unit load on the surface of the rail transit, t / m²; F: the surface area of the rail transit, m².

[0014] As a preferred embodiment of the present invention, the settlement coefficient K is determined according to the elastic modulus E and Poisson's ratio u of the rail transit foundation material:

[0015] K = 1.8(G / E)¹ / ² + 2.8(μ / E)¹ / ³;

[0016] Where: G is the elastic modulus of the rail transit foundation material, Pa; E is the elastic modulus, Pa; u is Poisson's ratio.

[0017] As a preferred embodiment of the present invention, in S2, for the drone data acquisition route, the following steps are included:

[0018] S4. Input data preparation: including the position coordinates of the take-off point and the target point, the performance parameters of the drone, and the environmental conditions;

[0019] S5. Selection of the trajectory planning algorithm: According to the needs of the task, the fuzzy logic control algorithm is used to calculate the flight trajectory of the drone and generate the flight route of the drone;

[0020] S6. Verification of the planning result: Verify the generated flight route to ensure that it meets the task requirements and safety requirements, and verify it through simulation experiments and actual flight methods to evaluate the effectiveness and feasibility of the fuzzy logic control algorithm.

[0021] As a preferred embodiment of the present invention, in S5, for the fuzzy logic control algorithm, first determine the fuzzy sets of the input and output variables, including the state parameters and environmental parameters of the drone aircraft,

[0022] The state parameters of the drone aircraft include flight parameters, signal parameters, and data acquisition camera parameters.

[0023] Among them,

[0024] The flight parameters include: flight altitude, flight distance, flight speed, and flight status;

[0025] The signal parameters include: GPS signal, remote control signal quality, and drone battery level;

[0026] The data acquisition camera parameters include: storage space, shooting parameters, and gimbal status.

[0027] As a preferred embodiment of the present invention, among the flight parameters, the flight altitude is the altitude of the drone relative to the takeoff location, and the flight distance is the distance of the drone relative to the takeoff point.

[0028] Among them, the flight states include ascending, descending, advancing, and retreating.

[0029] As a preferred embodiment of the present invention, among the signal parameters, the shooting parameters include resolution, frame rate, color temperature, exposure compensation, shutter speed, aperture, ISO, white balance, and focus settings.

[0030] Compared with the prior art, the above one or more technical solutions have the following beneficial effects:

[0031] In the drone acquisition method based on urban rail transit engineering monitoring, the method of using drones for acquisition can cover a large area in a short time, greatly improving the detection efficiency. The high-resolution imaging device provides real-time high-definition images and videos, providing strong support for data processing. At the same time, the drone flies in a way that adopts the fuzzy logic control algorithm, and can conduct real-time monitoring of the settlement area of the rail transit project in areas with dense high-rise buildings. On the one hand, it ensures the safety of the drone flight. On the other hand, the radio signal of the drone will not be greatly interfered, ensuring the normal transmission of the drone remote control signal and enhancing the safety of the drone during flight. Brief Description of the Drawings

[0032] The specification drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention.

[0033] Figure 1 is the drone flight trajectory diagram of the present invention; Figure 2 is the schematic diagram of the settlement curve of the present invention. Detailed Embodiments

[0034] To enable those skilled in the art to understand the features and effects of the present invention, the following is a general description and definition of the terms and phrases mentioned in the specification and claims. Unless otherwise specified, all technical and scientific terms used herein shall have the ordinary meaning understood by those skilled in the art regarding the present invention. When there are conflicting situations, the definition in this specification shall prevail.

[0035] The theories or mechanisms described and disclosed herein, whether right or wrong, shall not in any way limit the scope of the present invention, that is, the content of the present invention can be implemented without being limited by any specific theory or mechanism.

[0036] In this document, all features defined in the form of numerical ranges or percentage ranges, such as numerical values, quantities, contents, and concentrations, are only for the sake of brevity and convenience. Accordingly, the description of numerical ranges or percentage ranges should be regarded as having covered and specifically disclosed all possible sub-ranges and individual numerical values (including integers and fractions) within the ranges.

[0037] In this document, unless otherwise specified, the terms "comprising", "including", "containing", "having", or similar terms cover the meanings of "consisting of" and "consisting essentially of". For example, "A comprises a" covers the meanings of "A comprises a and others" and "A consists only of a".

[0038] In this document, for the sake of brevity of description, all possible combinations of all technical features in each embodiment or example are not described. Therefore, as long as there is no contradiction in the combination of these technical features, the technical features in each embodiment or example can be combined arbitrarily, and all possible combinations should be considered as falling within the scope described in this specification.

[0039] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of this application.

[0040] Conventional instruments and equipment in the art are used in the following embodiments. For the experimental methods without specific conditions noted in the following embodiments, they are usually carried out under conventional conditions or according to the conditions recommended by the manufacturers. Various raw materials are used in the following embodiments. Unless otherwise stated, commercially available products are used, and their specifications are conventional specifications in the art. In the specification of the present invention and the following embodiments, unless otherwise specified, "%" represents weight percentage, "parts" represents weight parts, and the ratio represents weight ratio.

[0041] Please refer to Figure 1 , the present invention discloses a method for collecting data by an unmanned aerial vehicle (UAV) based on the monitoring of urban rail transit projects, including the following steps:

[0042] S1. Use UAV radar scanning and oblique photogrammetry techniques to establish a ground three-dimensional model, compare the ground settlement changes at different construction stages of rail transit construction, and verify the accuracy and reliability by comparing the UAV data with the traditional manual monitoring data;

[0043] S2. Determine the technical requirements for the UAV data acquisition route and scope according to the deformation law and scope of the settlement area for different construction methods;

[0044] S3. Taking an engineering example as the background, establish a data model based on UAV technology for the collapse warning standard in rail transit engineering.

[0045] The data acquisition method using UAV radar scanning and oblique photogrammetry technology is the elastic model method. The K-value surface area ratio is used to estimate and calculate the settlement of the rail transit foundation.

[0046] Among them, it is assumed that the rail transit foundation is a brittle material. According to the principle of volume stability, when a load occurs on the rail transit foundation, the settlement amount s of the rail transit foundation can be expressed as:

[0047] s = K·q / F;

[0048] Among them: s: the settlement amount of the rail transit foundation, m; K: the settlement coefficient, m / t; q: the unit load on the surface of the rail transit, t / m²; F: the surface area of the rail transit, m².

[0049] The settlement coefficient K is determined according to the elastic modulus E and Poisson's ratio u of the rail transit foundation material:

[0050] K = 1.8(G / E)¹ / ² + 2.8(μ / E)¹ / ³;

[0051] Among them: G is the elastic modulus of the rail transit foundation material, Pa; E is the elastic modulus, Pa; u is Poisson's ratio.

[0052] In addition, for the UAV data acquisition route, it includes the following steps:

[0053] S4. Input data preparation: including the position coordinates of the take-off point and the target point, the performance parameters of the UAV, and the environmental conditions;

[0054] S5. Selection of the trajectory planning algorithm: According to the needs of the task, use the fuzzy logic control algorithm to calculate the UAV flight trajectory and generate the UAV flight route;

[0055] S6. Verification of the planning result: Verify the generated flight route to ensure that it meets the task requirements and safety requirements, and verify through simulation experiments and actual flight methods to evaluate the effectiveness and feasibility of the fuzzy logic control algorithm.

[0056] For the fuzzy logic control algorithm, first determine the fuzzy sets of the input and output variables, including the state parameters of the UAV aircraft and the environmental parameters.

[0057] The state parameters of the UAV aircraft include flight parameters, signal parameters, and data acquisition camera parameters.

[0058] Among them,

[0059] The flight parameters include: flight altitude, flight distance, flight speed, and flight status;

[0060] The signal parameters include: GPS signal, remote control signal quality, and drone battery level;

[0061] The data acquisition camera parameters include: storage space, shooting parameters, and gimbal conditions.

[0062] Among the flight parameters, the flight altitude is the height of the drone relative to the takeoff location, and the flight distance is the distance of the drone relative to the takeoff point.

[0063] Among them, the flight status includes ascending, descending, moving forward, and moving backward.

[0064] Among the signal parameters, the shooting parameters include resolution, frame rate, color temperature, exposure compensation, shutter speed, aperture, ISO, white balance, and focus settings.

[0065] After the drone flight data is collected, the foundation settlement deformation mainly includes the following factors:

[0066] 1. Geological factors: Soft foundation soil, insufficient bearing capacity, or improper foundation treatment, such as insufficient compaction or reinforcement, may all lead to foundation settlement. In addition, uneven thickness and inconsistent hardness of the foundation soil layer, or under eccentric load, are also prone to uneven settlement. There may be cavity or karst geological structures under the foundation, further affecting the foundation bearing capacity.

[0067] 2. Groundwater level change: The rise or fall of the groundwater level may cause the foundation soil to expand or contract, thereby triggering building settlement. Especially when the groundwater level drops, the pore water pressure inside the soil will decrease, thus accelerating the settlement of the soil mass.

[0068] 3. Building weight and load: If the foundation bearing capacity is not fully considered during design or construction, resulting in the building weight exceeding the foundation's bearing range, or the internal load distribution of the building is uneven, it may cause excessive local bearing pressure on the foundation, thereby generating settlement deformation.

[0069] 4. Construction factors: Improper foundation treatment and non-standard foundation construction behaviors will all pose potential risks to foundation settlement problems. In addition, excavation and piling construction activities may also affect the stability of the building foundation;

[0070] 5. Other external factors: Adjacent buildings being too close or demolishing surrounding buildings may affect the foundation stability. Earthquakes, landslides and other natural disasters, as well as the damage to the foundation soil layer caused by the growth of plant roots, may also lead to foundation settlement deformation.

[0071] The present invention mainly analyzes geological factors, groundwater level changes, and building weight and load factors.

[0072] 1) Regarding geological factors, the settlement performance of soil refers to the ability of the soil structure to undergo plastic deformation due to changes in soil moisture content under certain conditions. In engineering construction, the settlement performance of soil is one of the important indicators for evaluating the stability and deformation characteristics of soil masses. When the soil is subjected to external loads, compression and settlement of the soil mass occur due to the friction between particles and the viscous force between particles and water. Compression refers to the reduction in the spacing between particles within the soil mass, while settlement refers to the phenomenon of the overall sinking of the soil mass.

[0073] Settlement index

[0074] The settlement index is an important parameter for evaluating the engineering properties of soil. Commonly used settlement indices include the void ratio compression index (Cc) and the compression index (Cs). The void ratio compression index (Cc) refers to the compression deformation that occurs when the void ratio of the soil mass is reduced by a unit amount. The compression index (Cs) refers to the compression deformation that occurs to the overall soil mass while the void ratio changes.

[0075] 1. Experimental steps

[0076] 1. Prepare the test equipment and soil samples, and determine the test parameters, such as the effective consolidation stress and the test temperature.

[0077] 2. Place the soil sample in the compression device and apply a certain consolidation stress.

[0078] 3. Gradually increase the pressure and record the settlement amount of the soil sample at each pressure.

[0079] 4. Draw the settlement curve at different pressures based on the experimental data.

[0080] Calculate the void ratio compression index (Cc) and the compression index (Cs) based on the settlement curve.

[0081] 2. The settlement curve drawn based on the experimental data is as described in the Figure 2 specification:

[0083] It can be found from the curve graph that as the applied consolidation stress increases, the settlement amount of the soil gradually increases. This indicates that the soil has a certain settlement performance. And when the consolidation stress is small, the settlement amount is small and the deformation degree of the soil mass is small; while when the consolidation stress is large, the settlement amount is large and the deformation degree of the soil mass is large.

[0084] 2) Regarding groundwater level changes and building weight and load, the causes and mechanisms are separately described for the groundwater level decline caused by groundwater extraction and the ground settlement caused by surface load effects.

[0085] According to the principle of effective stress, σ = σ' + u, where σ' is the effective stress of the soil, u is the pore water pressure, and σ is the total stress. Assuming that the total stress in the soil layer remains unchanged during the pumping process, the decrease in pore water pressure will inevitably lead to an equal increase in the effective stress in the soil, resulting in proportional consolidation of the soil layer. The effective stress increase at the water level is a constant below the water level drop position. For the settlement calculation formula of multiple rock and soil layers:

[0086] Calculation formula for cohesive soil and silt: s = p0·h·a / (1 + e);

[0087] Calculation formula for sand: = p0·h / esi.

[0088] 1. Analysis of ground settlement caused by foundation additional stress

[0089] Similar to the groundwater level drop, the additional stress at the foundation bottom causes ground settlement. However, its distribution is different from that of the water level drop. The additional stress in the bearing layer mainly decreases with the increase in depth within a certain range of the foundation bottom. Beyond a certain depth, the additional stress is very small compared to the self-weight stress of the soil. For urban high-rise and super high-rise buildings, the influence of the additional stress and its impact on surrounding buildings within a certain range cannot be ignored, and sometimes it can even be destructive.

[0090] 2. Comparison of ground settlement caused by groundwater level drop and foundation additional stress

[0091] Since the causes of ground settlement are different, the degree and scope of settlement are also different. Only by clarifying the causes of various settlements and mastering their occurrence and development laws can we carry out targeted prevention and treatment. The following analyzes the settlements caused by the above two factors.

[0092] 2.1 Differences

[0093] Ground settlement caused by groundwater level drop:

[0094] 1. Cause: Groundwater level drops, pore water pressure decreases, the effective self-weight stress of the soil increases, and additional stress is generated.

[0095] 2. Action form of additional stress: Equivalent to a uniformly distributed load, and it increases linearly with the increase in depth within the groundwater change range, reaches the maximum at the changed water level and remains constant with the increase in depth.

[0096] 3. Scope: Large horizontal area, several square kilometers or even up to hundreds of square kilometers. Vertically, it exists until the non-compressible layer (such as bedrock).

[0097] 4. Relationship with formation esi: Inversely proportional to esi, and related to the compression within the entire compression layer range

[0098] It is related to the shrinkage modulus.

[0099] 5. Influence depth: The entire formation sinks as a whole, extending all the way to the bedrock surface. The deeper the bedrock, the greater the settlement.

[0100] 6. Treatment difficulty and preventive measures: The treatment difficulty is great and it cannot be restored. Restrict the overexploitation of groundwater and take recharge measures.

[0101] Ground settlement caused by the additional stress at the building foundation:

[0102] 1. Causes: The additional stress caused by the action of external concentrated loads or uniform loads transmitted to below the ground surface.

[0103] 2. Action form of the additional stress: It is equivalent to a concentrated load in a semi-infinite space. The additional stress decreases with the increase of depth as shown in the figure. When it reaches a certain depth, the influence can be ignored.

[0104] 3. Scope: Horizontally, it decreases rapidly away from the building. Vertically, it decreases with the increase of depth and can be ignored at a certain depth.

[0105] 4. Relationship with the formation esi: It is inversely proportional to esi, and has a great relationship with the compression modulus of the surface formation. The smaller the compression modulus, the thicker the soil layer, and the greater the settlement. Since the additional stress in the deep part is relatively small, the relationship with the compression modulus of the deep soil layer is relatively small.

[0106] 5. Influence depth: A certain depth within the influence range of the additional stress. Generally, it is calculated according to the additional stress equal to 0.2 times the self-weight stress of the formation, and for soft soil, it is calculated according to 0.1 times.

[0107] 6. Treatment difficulty and preventive measures: The treatment difficulty is relatively small. Smaller loads can be used, the foundation form can be optimized to reduce the vertical load, the deep formation can be utilized, or compensated design can be adopted.

[0108] 2.2. Similarities

[0109] 1. The ground settlement calculation method is the same, that is, the layerwise summation method. Since the additional stress under the foundation is a curve decrease, the average additional stress coefficient is used in the calculation process.

[0110] 2. The consolidation process is the same. The ground settlement process is a relatively long process, and the ground settlement develops continuously with time. The basic theory is the one-dimensional consolidation theory (vertical).

[0111] Limited to this, any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, making equivalent substitutions or changes, should be covered within the protection scope of the present invention.

Claims

1. A drone data collection method based on urban rail transit engineering monitoring, characterized in that: The following steps are involved: S1. Use drone radar scanning and oblique photogrammetry technology to build a three-dimensional ground model, compare the changes in ground settlement at different construction stages of rail transit construction, and compare drone data with traditional manual monitoring data to verify accuracy and reliability; S2. According to the deformation law and range of the settlement area of ​​different construction methods, research and determine the technical requirements for the route and range of drone data collection; S3. Based on engineering examples, a data model for the early warning standard of rail transit engineering collapse is established based on UAV technology.

2. The method for collecting data using a drone based on urban rail transit project monitoring according to claim 1 is characterized in that: In S1, the data collection method using drone radar scanning and oblique photogrammetry technology is an elastic model method, and the K value surface area ratio is used to estimate and calculate the rail transit foundation settlement. Among them, it is assumed that the rail transit foundation is a brittle material. According to the volume stability principle, when a load occurs on the rail transit foundation, the rail transit foundation settlement s can be expressed as: s = K·q / F; Where: s: rail transit foundation settlement, m; K: settlement coefficient, m / t; q: rail transit surface unit load, t / m2; F: rail transit surface area, m2.

3. The method for collecting data using a drone based on urban rail transit engineering monitoring according to claim 2 is characterized in that: The settlement coefficient K is determined according to the elastic modulus E and Poisson's ratio u of the rail transit foundation material: K=1.8(G / E)1 / 2+2.8(μ / E)1 / 3; Where: G is the elastic modulus of the rail transit foundation material, Pa; E is the elastic modulus, Pa; u is the Poisson's ratio.

4. The method for collecting data using a drone based on urban rail transit engineering monitoring according to claim 1 is characterized in that: In S2, for the drone data collection route, the following steps are included: S4. Input data preparation: including the location coordinates of the take-off point and the target point, the performance parameters of the UAV and the environmental conditions; S5, trajectory planning algorithm selection: according to the needs of the task, the fuzzy logic control algorithm is used to calculate the UAV flight trajectory and generate the UAV flight route; S6. Verification of planning results: Verify the generated flight route to ensure that it meets the mission requirements and safety requirements. Verify through simulation experiments and actual flight methods to evaluate the effectiveness and feasibility of the fuzzy logic control algorithm.

5. The method for collecting data using a drone based on urban rail transit project monitoring according to claim 4 is characterized in that: In S5, for the fuzzy logic control algorithm, the fuzzy set of input and output variables is first determined, including the state parameters and environmental parameters of the UAV aircraft, The status parameters of the UAV aircraft include flight parameters, signal parameters and data acquisition camera parameters. in, Flight parameters include: flight altitude, flight distance, flight speed and flight status; Signal parameters include: GPS signal, remote control signal quality and drone battery level; Data collection camera parameters include: storage space, shooting parameters and gimbal status.

6. The method for collecting data using unmanned aerial vehicles based on urban rail transit project monitoring according to claim 5 is characterized in that: Among the flight parameters, the flight altitude is the height of the drone relative to the take-off point, and the flight distance is the distance of the drone relative to the take-off point. Among them, the flight status includes ascending, descending, forward and backward.

7. The method for collecting data using unmanned aerial vehicles based on urban rail transit project monitoring according to claim 5 is characterized in that: Among the signal parameters, the shooting parameters include resolution, frame rate, color temperature, exposure compensation, shutter speed, aperture, ISO, white balance and focus settings.

Images