Method for unmanned aerial vehicle to autonomously plan and cruise according to specific weather of seawall

Abstract

The invention discloses a method for autonomous route planning and cruising of an unmanned aerial vehicle according to specific weather of a seawall, and aims to improve seawall inspection efficiency and safety. The method comprises the following steps: firstly, acquiring weather data of a seawall area in real time through a meteorological sensor, and dividing weather conditions into different grades after preprocessing; and then, according to the current weather level, dynamically adjusting the cruise route of the unmanned aerial vehicle, considering historical inspection data and seawall safety risk assessment in route planning, setting a key inspection area, and improving the inspection precision. In the cruising process of the unmanned aerial vehicle, inspection data such as images, videos, temperature and humidity of the seawall are collected through equipment such as a camera and a sensor. And finally, processing and analyzing the collected data, generating an inspection report, and timely discovering potential safety hazards of the seawall. The method can autonomously plan the route according to the specific weather condition of the seawall, improves the inspection efficiency, adapts to the complex weather environment, reduces the safety risk, and achieves the intelligentization and automation of seawall inspection.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of unmanned aerial vehicle control, and specifically relates to a method for autonomous route planning and cruising of an unmanned aerial vehicle according to specific weather conditions of a seawall. BACKGROUND

[0002] The seawall is an important barrier for protecting coastal areas, and its safe operation is crucial for the safety of people's lives and property. The traditional seawall inspection method mainly relies on manual inspection, which is inefficient, costly and has safety risks. Using unmanned aerial vehicles for seawall inspection can effectively improve inspection efficiency, reduce inspection costs, and avoid personnel safety risks.

[0003] However, existing unmanned aerial vehicle inspection methods usually use preset routes, which are difficult to adapt to the complex and variable weather conditions of the seawall area, such as wind speed, wind direction, rainfall, etc., resulting in poor inspection results and even safety risks. At the same time, existing unmanned aerial vehicle route planning methods also rarely consider the special geographical environment and inspection needs of the seawall, and cannot achieve efficient autonomous cruising.

[0004] Therefore, there is an urgent need for a method of unmanned aerial vehicle that can autonomously plan and cruise according to specific weather conditions of a seawall. SUMMARY

[0005] The purpose of the present application is to overcome the shortcomings of the prior art and provide a method of unmanned aerial vehicle that can autonomously plan and cruise according to specific weather conditions of a seawall, in order to improve the efficiency and safety of seawall inspection.

[0006] The technical solution used in the present application is: a method for autonomous route planning and cruising of an unmanned aerial vehicle according to specific weather conditions of a seawall, comprising the following steps: weather data acquisition, weather data preprocessing, weather grade division, route planning, unmanned aerial vehicle cruising, data processing and analysis.

[0007] Further, weather data acquisition: real-time acquisition of weather data in the seawall area through meteorological sensors, network data interfaces, etc., including but not limited to wind speed, wind direction, rainfall, temperature, humidity, etc.

[0008] Further, weather data preprocessing: preprocessing of the acquired weather data, including data cleaning, data calibration, data filtering, etc., to eliminate noise interference and ensure the accuracy and reliability of the data.

[0009] Further, weather grade division: according to the preprocessed weather data, the weather conditions are divided into different grades, for example: First-class weather: wind speed less than 5m / s, no rainfall, suitable for routine cruising.

[0010] Secondary weather: Wind speed between 5m / s - 10m / s, with light rain, suitable for low-speed cruising.

[0011] Tertiary weather: Wind speed greater than 10m / s, with moderate to heavy rain, not suitable for cruising.

[0012] Further improvement lies in route planning: Basic route generation: According to the geographical information of the seawall, pre-generate the basic cruising route.

[0013] Dynamic route adjustment: According to the current weather level, dynamically adjust the cruising route. For example: Primary weather: Use the basic cruising route to cruise at a faster speed.

[0014] Secondary weather: Adjust the flight altitude, appropriately reduce the cruising speed, and adjust the route direction according to the wind direction to ensure flight stability and inspection effect.

[0015] Tertiary weather: Suspend cruising, or return to the take-off point and wait for the weather to improve.

[0016] Further, the key area of inspection is set: In the route planning, according to the historical inspection data and seawall safety risk assessment, set the key inspection area, and increase the cruising density in these areas.

[0017] Further, the unmanned aerial vehicle cruising includes: autonomous navigation, real-time monitoring, and abnormal handling; Autonomous navigation: The unmanned aerial vehicle autonomously navigates according to the planned route.

[0018] Real-time monitoring: Real-time monitoring of the flight state and surrounding environment of the unmanned aerial vehicle through sensors.

[0019] Abnormal handling: In the process of cruising, if an emergency situation (such as low battery, equipment failure, sudden weather change, etc.) occurs, start the emergency plan, such as automatic return, forced landing, etc.

[0020] Further, the inspection data collection: Through the camera, sensor and other equipment carried, the image, video, temperature, humidity and other inspection data of the seawall are collected.

[0021] Further, data processing and analysis: Process and analyze the collected inspection data, generate an inspection report, and timely discover potential safety hazards of the seawall.

[0022] The beneficial effects of the present invention compared with the prior art are: 1. The present invention collects the image, video, temperature, humidity and other inspection data of the seawall through the camera, sensor and other equipment carried by the unmanned aerial vehicle during cruising.

[0023] The application improves the inspection efficiency, adapts to complex weather environment, reduces safety risks, realizes the intelligentization and automation of seawall inspection by autonomously planning a route according to specific weather conditions of the seawall. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 The application is an automatic cruise planning route design process schematic diagram.

[0025] Figure 2 The application is a schematic diagram of the unmanned aerial vehicle cruise initiation process. DETAILED DESCRIPTION

[0026] The application will be further described in detail below in combination with specific embodiments.

[0027] Example 1: Unmanned aerial vehicle system configuration: select a four-rotor or six-rotor unmanned aerial vehicle with good wind resistance. The unmanned aerial vehicle should have sufficient load capacity to carry the required sensors and equipment and ensure the cruise endurance time.

[0028] The unmanned aerial vehicle should be equipped with a reliable flight control system and a fault protection mechanism.

[0029] Flight control system: use mature open source flight control firmware (for example: PX4 or ArduPilot), or independently developed flight control system. The flight control system should have the functions of autonomous navigation, path planning, attitude control, height control, etc. The flight control system should support communication with the ground control station to realize real-time data transmission and remote control.

[0030] Power system: use high-efficiency brushless motors and propellers to ensure the flight performance and endurance time of the unmanned aerial vehicle. Equip with high-capacity intelligent lithium batteries to provide stable power supply.

[0031] Communication system: use 2.4GHz or 5.8GHz digital radio communication link to ensure stable and reliable communication between the unmanned aerial vehicle and the ground control station. Optionally, a 4G / 5G cellular network module can be used as a backup communication link.

[0032] Onboard power supply: equip with an independent power management system to ensure stable power supply to each module.

[0033] Example 2: Sensor configuration: wind speed and direction sensor: choose ultrasonic or cup-type wind speed and direction sensor with high accuracy and fast response.

[0034] Rainfall sensor: choose a rain gauge or light-sensitive rainfall sensor that can measure rainfall intensity.

[0035] Temperature and humidity sensor: High-precision temperature and humidity sensor is selected to measure the ambient temperature and humidity.

[0036] Barometric pressure sensor: High-precision barometric pressure sensor is selected to assist in height control and weather data analysis.

[0037] Visual sensor: High-definition camera: 1080P or 4K resolution camera is selected to capture images and video data of the seawall.

[0038] Thermal imaging camera: Thermal imaging camera can be selected to detect temperature anomalies on the seawall surface.

[0039] Positioning sensor: High-precision GPS module is selected for UAV positioning and navigation.

[0040] Inertial measurement unit (IMU): High-precision IMU is selected to measure the attitude and acceleration of the UAV.

[0041] Other sensors: Laser radar (LiDAR): LiDAR can be selected for high-precision three-dimensional map construction. Gas sensor: Gas sensor can be selected to detect harmful gases in the environment.

[0042] Example 3: Weather data processing: Real-time collection of meteorological data through sensors, such as wind speed (m / s), wind direction (angle), rainfall (mm / h), temperature (℃), humidity (%), and atmospheric pressure (hPa).

[0043] Data preprocessing: Data cleaning: Eliminate abnormal data, such as values beyond the sensor range and obvious noise interference. Data calibration: Calibrate the collected data according to the calibration parameters of the sensor to improve data accuracy.

[0044] Data filtering: Use Kalman filtering or moving average filtering algorithms to smooth the data and eliminate noise.

[0045] Weather classification: First-level weather: wind speed <5m / s, rainfall <1mm / h (or no rainfall).

[0046] Second-level weather: 5m / s≤wind speed≤10 m / s, 1mm / h≤rainfall≤5mm / h (or light rain).

[0047] Third-level weather: wind speed >10m / s, rainfall >5mm / h (or moderate to heavy rain).

[0048] The weather classification criteria can be adjusted according to actual conditions.

[0049] Example 4: Route planning algorithm: According to the GPS coordinate information of the seawall, generate a route along the seawall contour, including straight line segments and arc line segments.

[0050] The route can be represented in the form of a waypoint list. The height of the route can be set, for example, 10-20 meters above the seawall surface.

[0051] Dynamic adjustment of the route: Primary weather: no adjustment, directly use the basic route.

[0052] Secondary weather: wind speed adjustment: according to the wind speed, appropriately reduce the cruising speed, for example: basic speed * (1 - wind speed / 15). Wind direction adjustment: adjust the route direction according to the wind direction, for example: when flying against the wind, slightly offset to the side to reduce the resistance of the wind. Height adjustment: slightly lower the flight height, for example, reduce 2-5 meters, to reduce the influence of the wind.

[0053] Tertiary weather: Pause cruising, and start the automatic return program. If the current position is far from the take-off point, fly to the nearest safe landing point first.

[0054] Inspection of key areas: through the map editor, set the key inspection area on the ground control station.

[0055] The key inspection area can be determined according to historical inspection data, seawall safety risk assessment, manual inspection experience, etc. In the route planning process, increase the density of waypoints in the key inspection area, or reduce the flight speed to improve the inspection quality.

[0056] Example 5: Unmanned aerial vehicle flight control: the unmanned aerial vehicle uses GPS and IMU for autonomous navigation according to the planned route. The flight control system controls the flight attitude, speed and height of the unmanned aerial vehicle according to the current position and target waypoint.

[0057] Real-time monitoring: through the ground control station, real-time monitoring of the flight state of the unmanned aerial vehicle, including position, speed, height, attitude, power and other information. Real-time reception of sensor data and video data transmitted by the unmanned aerial vehicle.

[0058] Abnormal handling: low power: when the power is lower than the preset threshold, start the automatic return program. Device failure: when the sensor or motor fails, start the emergency plan, for example: automatic landing, emergency return, etc. Communication interruption: when the communication link is interrupted, the unmanned aerial vehicle switches to autonomous flight mode and tries to re-establish the connection.

[0059] Weather Mutation: When the weather level changes suddenly, immediately adjust the route or start the return procedure.

[0060] Inspection Data Collection: During the cruise, the camera collects image and video data regularly or on demand. Weather sensors collect weather data in real time. Other sensors collect data at a preset frequency.

[0061] Example 6: Data Processing and Analysis: Data Storage: Store the collected image, video, weather and other data in local storage or cloud server.

[0062] Data Processing: Image Processing: Use image recognition algorithms to detect cracks, damage, deformation and other abnormal conditions of seawalls. Video Processing: Use video analysis algorithms to detect rising water levels, overflow and other abnormal conditions of seawalls.

[0063] Weather Data Analysis: Analyze weather data to assess the risk level of the seawall area.

[0064] Inspection Report Generation: Generate an inspection report, including: inspection time, inspection range, abnormal conditions, risk assessment, inspection photos and videos, etc. The inspection report can be output in multiple formats (e.g.: PDF, HTML, Excel).

[0065] Data Visualization: Visualize the inspection data and inspection report in charts, maps, images, etc.

[0066] Data Sharing: Share the inspection report with relevant management departments to take timely maintenance measures.

[0067] Software Implementation.

Claims

1. A method for autonomous route planning and cruising of unmanned aerial vehicles (UAVs) based on specific weather conditions along a seawall, characterized in that, Includes the following steps: Weather data acquisition, weather data preprocessing, weather level classification, flight route planning, drone patrol, data processing and analysis.

2. The method according to claim 1, characterized in that, The weather data includes wind speed, wind direction, rainfall, temperature, and humidity.

3. The method according to claim 1, characterized in that, The weather levels are divided into Level 1, Level 2, and Level 3.

4. The method according to claim 3, characterized in that, Level 1 weather refers to wind speed less than 5 m / s with no rainfall; Level 2 weather refers to wind speed between 5 m / s and 10 m / s with light rain; Level 3 weather refers to wind speed greater than 10 m / s with moderate to heavy rain.

5. The method according to claim 1, characterized in that, The route planning includes basic route generation and dynamic route adjustment, which involves adjusting the cruise route based on the current weather level.

6. The method according to claim 5, characterized in that, The dynamic adjustment of the flight path includes: using the basic cruise route and cruising at a relatively high speed in Level 1 weather; adjusting the flight altitude, appropriately reducing the cruise speed, and adjusting the flight path direction according to the wind direction in Level 2 weather; suspending cruise or returning to the takeoff point in Level 3 weather.

7. The method according to claim 1, characterized in that, In the route planning, key inspection areas are set based on historical inspection data and seawall safety risk assessment.

8. The method according to claim 1, characterized in that, The drone patrol includes autonomous navigation, real-time monitoring, anomaly handling, and inspection data collection.

9. The method according to claim 1, characterized in that, The data processing and analysis includes generating inspection reports.

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