A wind farm line inspection system and method based on a vehicle-mounted drone nest

Abstract

The present invention belongs to the field of vehicle-mounted UAV applications, and provides a UAV wind farm line inspection system and method based on a vehicle-mounted machine nest, including: a carrier vehicle for carrying a vehicle-mounted machine nest and a computer to perform inspection tasks; a vehicle-mounted machine nest for controlling the flight of the UAV and the endurance of the UAV; a vehicle-mounted computer for transmitting information and planning routes; and a UAV equipped with multiple sensors to collect wind farm line information. The present invention is used for wind farm line inspection and wind farm line fault inspection. The present invention realizes the application of a vehicle-mounted UAV system in wind farm line inspection, reduces the wind farm inspection cost, improves the inspection efficiency of the vehicle-mounted UAV system, and ensures the stable operation of the wind farm.

Description

Technical Field

[0001] The present invention relates to the application field of vehicle-mounted UAVs, and in particular to a UAV wind farm inspection system and method based on a vehicle-mounted machine nest. Background Art

[0002] The scale of wind farms is getting bigger and bigger. The operation of wind farms is accompanied by many equipment failures and equipment aging. There are many possible fault points in large-scale wind farms. Once a wind farm fails, if it is not handled in time, it will cause a series of safety problems or even large-scale power outages. Therefore, wind farms need to be inspected regularly to ensure the safe and stable operation of wind farms. Wind farms are generally located in remote areas with harsh geographical environments. At the same time, with the increase in the scale of wind power, the traditional manual inspection mode is not only costly, labor-intensive, and inefficient, but also difficult to fully and timely discover problems, and the degree of intelligence is also low.

[0003] Drones have a clear high-altitude vision and can conduct inspections efficiently and quickly. They can also carry high-definition cameras, infrared cameras, laser scanners, recording devices, fire bombs and other equipment to conduct flight inspections of wind turbines and wind farm transmission lines. However, the endurance and control of drones require drone nests. Due to the large area and complex environment of wind farms, if a drone nest is installed in a wind farm, not only will the cost of the nest be too high, but the maintenance and repair of the nest will also be expensive. The vehicle-mounted drone system has the advantages of low cost, high efficiency, large inspection range and no need for professional pilots.

[0004] In the field of vehicle-mounted drone inspections, the "Vehicle-mounted UAV intelligent inspection operation system and method" with patent number CN202011440286.7 improves the efficiency of the vehicle-mounted UAV system and the accuracy of UAV control, and the "A power distribution network inspection UAV based on a vehicle-mounted system" with patent number CN202011495213.8 improves the maneuverability and movement accuracy of the vehicle-mounted UAV. However, these two patents only improve the device performance of the vehicle-mounted UAV system, and do not take into account the efficiency of the vehicle-mounted UAV inspection method.

[0005] To sum up, the inspection efficiency of the vehicle-mounted drone system can be improved by optimizing the vehicle-mounted drone inspection process, and the safety and stability of the vehicle-mounted drone inspection system can be ensured. Summary of the invention

[0006] The purpose of the present invention is to solve the problem of low efficiency of the current vehicle-mounted drone inspection process, and to provide a drone wind farm line inspection system and method based on a vehicle-mounted machine nest; the inspection efficiency of the vehicle-mounted drone is improved, and the safety of the vehicle-mounted drone system is improved.

[0007] A UAV wind farm line inspection system based on a vehicle-mounted machine nest, characterized in that it includes a vehicle-mounted machine nest, a UAV, a vehicle-mounted computer and a carrier vehicle;

[0008] The vehicle-mounted nest has the functions of automatic charging of drones, wireless contactless charging of drones by the vehicle-mounted nest, and charging of the vehicle-mounted nest by the vehicle-mounted power supply. In terms of external equipment, it has a vehicle-mounted nest radio, meteorological, external monitoring, RTKGNSS equipment and communication antenna fusion equipment. At the same time, the vehicle-mounted nest has its own battery to independently power the vehicle-mounted nest equipment and the drone charging time should be less than 2 hours without external power input. In good environment, the stable image transmission range between the vehicle-mounted nest and the drone is greater than 15 kilometers;

[0009] The UAV has a single battery life of more than 30 minutes, has RTKGNSS communication function, the communication distance between the UAV and the vehicle-mounted machine nest is more than 15 kilometers, supports the installation of a bottom-mounted dual-light gimbal, and the UAV can be equipped with a multi-spectral gimbal, which includes a visible light camera, an infrared thermal imager and a laser radar. The multi-spectral gimbal is used for line fault detection; the UAV has an automatic obstacle avoidance function and can automatically avoid obstacles in an emergency;

[0010] The on-board computer has an autonomous inspection function and can import inspection tasks. For inspection tasks, it can dynamically calculate the most suitable task path and number of inspections, and complete the task autonomously without human intervention. It has an inspection alarm function, which can realize automatic background alarm and regular analysis reports for problems such as local temperature anomalies and safety distance anomalies. The on-board computer has a breakpoint resumption function. During the inspection process, if the drone interrupts the mission and returns due to abnormal conditions, it can take off again and continue the inspection task from the breakpoint. The on-board computer has a precise landing function. After the drone returns autonomously, it can land accurately on the on-board machine nest. The on-board computer has a real-time monitoring function. The on-board machine nest uploads monitoring videos and internal and external environmental information to the on-board computer in real time. The on-board machine nest is wirelessly connected to the drone, and the on-board machine nest is connected to the on-board computer.

[0011] The transport vehicle can carry the vehicle-mounted machine nest and the UAV, the vehicle-mounted computer is installed in the transport vehicle, and has a certain mountain driving ability;

[0012] The wind farm master station has an information transmission function, which can send data and instructions to the on-board computer and receive image information from the on-board computer and flight data from the drone; the wind farm master station has a meteorological detection function, which can obtain real-time meteorological data in the wind farm environment and meteorological forecasts through the meteorological station arranged in the wind farm. The wind farm master station also has a wind farm fault detection function, which can detect whether a fault occurs by detecting the operating status of the wind farm equipment.

[0013] A patrol method for a wind farm line patrol system based on a vehicle-mounted drone nest comprises the following steps:

[0014] Step 1: The wind farm master station determines whether there is a fault in the wind farm line based on the operating status of the wind farm equipment. If there is no fault in the wind farm line, it will perform the ordinary wind farm inspection task. The on-board computer will use artificial intelligence algorithms to plan the car route, drone inspection route and drone take-off and landing points based on the imported task objectives, combined with the wind farm topographic map and real-time weather forecast of the wind farm. At the same time, the on-board computer will monitor the flight status of the drone in real time;

[0015] Step 2: The operation and maintenance personnel drive along the planned route and open the hatch of the vehicle-mounted nest at the planned drone take-off point. At this time, the drone takes off and performs the flight mission according to the planned flight route. During the mission, the drone collects multiple types of image information of the route and transmits it back to the vehicle-mounted computer, which performs intelligent fault diagnosis.

[0016] Step 3: After the operation and maintenance personnel release the drone at the take-off point, they drive directly to the next drone landing point and wait for the drone to land and charge. During this process, the distance between the drone and the carrier vehicle must not exceed the maximum communication distance;

[0017] Step 4: While the drone is charging, the operator needs to drive the transport vehicle to the next take-off point;

[0018] If the wind farm line fails, the on-board computer must cover the possible fault location of the wind farm line when planning the route. If the wind farm fails during the mission, the on-board computer will re-plan the inspection route covering the possible fault location based on the vehicle position of the transport vehicle and the position of the drone.

[0019] The on-board computer monitors weather data in real time. If the weather changes and is not suitable for the drone to fly, the on-board computer issues a warning message and plans the landing point of the drone in real time so that the drone can meet the vehicle in the shortest time. If the drone cannot continue to fly, the on-board computer issues an emergency landing instruction nearby.

[0020] The on-board computer monitors the flight status of the drone in real time. If the drone fails, the on-board computer issues a warning message and plans the landing point of the drone in real time so that the drone can meet the vehicle in the shortest time. If the drone cannot continue to fly due to a failure, the on-board computer issues an emergency landing instruction nearby.

[0021] The onboard computer of the drone will issue a return command only when the drone has insufficient battery life or is in poor condition, and the drone will otherwise remain in working condition;

[0022] The on-board computer uses artificial intelligence algorithms to plan car routes, drone inspection routes, and drone take-off and landing points. The artificial intelligence algorithms can accurately plan the routes of drones and vehicles in large-scale wind farms with complex environments.

[0023] When the drone is performing a mission, if it encounters an unknown obstacle on the drone inspection route, the drone can avoid the obstacle on its own and return to the drone inspection route after bypassing the obstacle. At the same time, the drone transmits the image and coordinates of the unknown obstacle to the onboard computer.

[0024] Beneficial effects: The present invention optimizes the vehicle-mounted UAV inspection process to improve the inspection efficiency of the vehicle-mounted UAV system. The vehicle-mounted computer uses artificial intelligence algorithms to plan car routes and UAV inspection routes according to the wind farm topographic map and real-time weather forecasts of the wind farm. At the same time, it monitors meteorological data and UAV operating status in real time. If any abnormality occurs, corresponding measures are taken immediately to ensure the safety and stability of the vehicle-mounted UAV inspection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is the structure of the vehicle-mounted UAV wind farm line inspection system.

[0026] Figure 2 It is a flow chart of wind farm line inspection using vehicle-mounted drone. DETAILED DESCRIPTION

[0027] In order to better understand the technical content of the present invention, specific embodiments are given and described as follows in conjunction with the accompanying drawings.

[0028] like Figure 1 As shown, a UAV wind farm line inspection system based on a vehicle-mounted machine nest includes a vehicle-mounted machine nest, a UAV, a vehicle-mounted computer, a carrier vehicle and a wind farm master station; the vehicle-mounted machine nest has the functions of automatic charging of the UAV, wireless non-contact charging of the UAV by the vehicle-mounted machine nest, and charging of the vehicle-mounted machine nest by the vehicle-mounted power supply; in terms of external equipment, it has a vehicle-mounted machine nest radio, meteorological, external monitoring, RTKGNSS equipment and communication antenna fusion equipment; at the same time, the vehicle-mounted machine nest has its own battery, which can independently power the vehicle-mounted machine nest equipment and the UAV charging time in the absence of external power input, and the stable image transmission range between the vehicle-mounted machine nest and the UAV is greater than 15 kilometers under good environment.

[0029] The drone has a single battery life of more than 30 minutes and has RTKGNSS communication function. The communication distance between the drone and the vehicle-mounted machine nest is more than 15 kilometers. It supports the installation of a downward dual-light gimbal. At the same time, the drone can be equipped with a multi-spectral gimbal, which includes a visible light camera, an infrared thermal imager and a laser radar. The multi-spectral gimbal is used for line fault detection; the drone also has an automatic obstacle avoidance function and can automatically avoid obstacles in an emergency.

[0030] The on-board computer has an autonomous inspection function. After the inspection task is imported, it can dynamically calculate the most suitable task path and inspection times for the inspection task, and complete the task autonomously without human intervention. The on-board computer has an inspection alarm function, which can realize automatic background alarm and regular analysis reports for problems such as local temperature anomalies and safety distance anomalies; the on-board computer has a breakpoint continuation function. During the inspection process, if the drone interrupts the task and returns due to abnormal conditions, it can take off again and continue the inspection task from the breakpoint; the on-board computer has a precise landing function. After the drone returns autonomously, it can land accurately on the on-board machine nest; the on-board computer has a real-time monitoring function. The on-board machine nest uploads the monitoring video and internal and external environmental information to the on-board computer in real time.

[0031] The transport vehicle is used to transport the vehicle-mounted machine nest and the UAV, and has a certain ability to travel in mountainous areas;

[0032] The wind farm master station has an information transmission function, which can send data and instructions to the on-board computer and receive image information from the on-board computer and flight data from the drone; the wind farm master station has a meteorological detection function, which can obtain real-time meteorological data in the wind farm environment and meteorological forecasts through the meteorological station arranged in the wind farm. The wind farm master station also has a wind farm fault detection function, which can detect whether a fault occurs by detecting the operating status of the wind farm equipment.

[0033] like Figure 2 As shown, the present invention discloses an inspection method of a wind farm line inspection system based on a vehicle-mounted drone nest, comprising the following steps:

[0034] Step 1: The wind farm master station determines whether there is a fault in the wind farm line according to the operating status of the wind farm equipment. If there is no fault in the wind farm line, it will perform the ordinary wind farm inspection task. The on-board computer will use artificial intelligence algorithms to plan the car route, the drone inspection route, and the take-off and landing points of the drone on the vehicle-mounted machine nest based on the imported task objectives, combined with the wind farm topographic map and the real-time weather forecast of the wind farm. At the same time, the on-board computer will monitor the flight status of the drone in real time;

[0035] Step 2: The operation and maintenance personnel drive along the planned route and open the hatch of the vehicle-mounted nest at the planned drone take-off point. At this time, the drone takes off and performs the flight mission according to the planned flight route. During the mission, the drone collects multiple types of image information of the route and transmits it back to the vehicle-mounted computer, which performs intelligent fault diagnosis.

[0036] Step 3: After the operation and maintenance personnel release the drone at the take-off point, they drive directly to the next drone landing point and wait for the drone to land and charge. During this process, the distance between the drone and the vehicle must not exceed the maximum communication distance;

[0037] Step 4: While the drone is charging, the operator needs to drive the car to the next take-off point.

[0038] If the wind farm line fails, the on-board computer must cover the possible fault location of the wind farm line when planning the route. If the wind farm fails during the mission, the on-board computer will re-plan the inspection route covering the possible fault location based on the vehicle position of the transport vehicle and the position of the drone.

[0039] The on-board computer monitors weather data in real time. If the weather changes and is not suitable for the drone to fly, the on-board computer issues a warning message and plans the landing point of the drone in real time so that the drone can meet the vehicle in the shortest time. If the drone cannot continue to fly, the on-board computer issues an emergency landing instruction nearby.

[0040] The on-board computer monitors the flight status of the drone in real time. If the drone fails, the on-board computer issues a warning message and plans the landing point of the drone in real time so that the drone can meet the vehicle in the shortest time. If the drone cannot continue to fly due to a failure, the on-board computer issues an emergency landing instruction nearby.

[0041] The onboard computer of the drone will issue a return command only when the drone has insufficient battery life or is in poor condition, and the drone will otherwise remain in working condition;

[0042] The on-board computer uses artificial intelligence algorithms to plan car routes, drone inspection routes, and drone take-off and landing points. The artificial intelligence algorithms can accurately plan the routes of drones and vehicles in large-scale wind farms with complex environments.

[0043] When the drone is performing a mission, if it encounters an unknown obstacle on the drone inspection route, the drone can avoid the obstacle on its own and return to the drone inspection route after bypassing the obstacle. At the same time, the drone transmits the image and coordinates of the unknown obstacle to the onboard computer.

[0044] In summary, although the present invention lists the above-mentioned preferred embodiments, it should be noted that although technicians in this field can make various changes and modifications, unless such changes and modifications deviate from the scope of the present invention, they should be included in the protection scope of the present invention.

Claims

1. A UAV wind farm line inspection system based on a vehicle-mounted machine nest, characterized in that: include: The vehicle-mounted nest has the functions of automatic charging of drones, wireless contactless charging of drones by the vehicle-mounted nest, and charging of the vehicle-mounted nest by the vehicle-mounted power supply. In terms of external equipment, it has a vehicle-mounted nest radio, meteorological, external monitoring, RTKGNSS equipment, and communication antenna fusion equipment. The vehicle-mounted nest has its own battery, which can independently power the vehicle-mounted nest equipment and charge the drone in less than 2 hours without external power input. The stable image transmission range between the vehicle-mounted nest and the drone is greater than 15 kilometers. A drone, wherein the single battery life of the drone is greater than 30 minutes, the drone has an RTKGNSS communication function, and the communication distance between the drone and the vehicle-mounted machine nest is greater than 15 kilometers. The drone supports the installation of a bottom-mounted dual-light gimbal. The drone can be equipped with a multi-spectral gimbal, wherein the multi-spectral gimbal includes a visible light camera, an infrared thermal imager, and a laser radar. The multi-spectral gimbal is used for line fault detection. The drone has an automatic obstacle avoidance function and can automatically avoid obstacles in an emergency; The on-board computer has an autonomous inspection function and can import inspection tasks. For inspection tasks, it can dynamically calculate the most suitable task path and inspection times, and complete the task autonomously without human intervention. The on-board computer has an inspection alarm function, which can realize automatic background alarm and regular analysis reports for local temperature anomalies and safety distance anomalies. The on-board computer has a breakpoint continuation function. During the inspection process, if the drone interrupts the mission and returns due to abnormal circumstances, it can take off again and continue the inspection task from the breakpoint. The on-board computer has a precise landing function. After the drone returns autonomously, it will land precisely on the on-board nest. The on-board computer has a real-time monitoring function. The on-board nest monitoring video and internal and external environmental information are uploaded to the on-board computer in real time. A transport vehicle, which is used to transport the vehicle-mounted machine nest and the UAV and has the ability to travel in mountainous areas, and the vehicle-mounted computer is installed on the transport vehicle; And a wind farm master station, which has an information transmission function and can send data and instructions to the on-board computer; the wind farm master station has a meteorological detection function and can obtain real-time meteorological data in the wind farm environment and meteorological forecasts through the meteorological station arranged in the wind farm; the wind farm master station has a wind farm fault detection function and can detect whether the wind farm line has a fault by detecting the operating status of the wind farm equipment.

2. An inspection method using a wind farm line inspection system based on a vehicle-mounted drone nest as claimed in claim 1, characterized in that: The following steps are involved: Step 1: The wind farm master station determines whether there is a fault in the wind farm line according to the operating status of the wind farm equipment. If there is no fault, it will perform the ordinary wind farm inspection task. The on-board computer will plan the transport vehicle route, the drone inspection route and the drone take-off and landing point according to the imported task objectives, combined with the wind farm topographic map and the wind farm real-time weather forecast. At the same time, the on-board computer will monitor the flight status of the drone in real time; Step 2: The operation and maintenance personnel drive along the planned route and open the hatch of the vehicle-mounted nest at the planned drone take-off point. At this time, the drone takes off and performs the flight mission according to the planned flight route. During the mission, the drone collects multiple types of image information of the route and transmits it back to the vehicle-mounted computer, which performs intelligent fault diagnosis. Step 3: After the operation and maintenance personnel release the drone at the take-off point, they drive directly to the next drone landing point and wait for the drone to land and charge. During this process, the distance between the drone and the carrier vehicle must not exceed the maximum communication distance; Step 4: While the drone is charging, the operator needs to drive the transport vehicle to the next take-off point.

3. The inspection method of the wind farm line inspection system based on the vehicle-mounted machine nest according to claim 2 is characterized in that: If a wind farm line fails, the on-board computer must cover the possible faulty parts of the wind farm line when planning the route. If a wind farm line fails during the mission, the on-board computer will re-plan the inspection route covering the possible faulty parts based on the vehicle position of the transport vehicle and the drone position.

4. The inspection method of the wind farm line inspection system based on the vehicle-mounted machine nest according to claim 2 is characterized in that: The on-board computer monitors meteorological data in real time. If the weather changes and is not suitable for drone flight, the on-board computer will issue a warning message and plan the drone landing point in real time so that the drone can meet the vehicle in the shortest time. If the drone cannot continue to fly, the on-board computer will issue an emergency landing command nearby.

5. The inspection method of the wind farm line inspection system based on the vehicle-mounted machine nest according to claim 2 is characterized in that: The on-board computer monitors the flight status of the drone in real time. If the drone malfunctions, the on-board computer will issue a warning message and plan the landing point of the drone in real time so that the drone can rendezvous with the vehicle in the shortest time. If the drone cannot continue to fly due to a malfunction, the on-board computer will issue an emergency landing command nearby.

6. The inspection method of the wind farm line inspection system based on the vehicle-mounted machine nest according to claim 2 is characterized in that: The onboard computer will only issue a return-to-nest command when the drone's battery life is insufficient or the drone's body is in poor condition. Otherwise, the drone remains in working condition.

7. The inspection method of the wind farm line inspection system based on the vehicle-mounted machine nest according to claim 2 is characterized in that: The on-board computer uses artificial intelligence algorithms to plan the routes of transport vehicles, drone inspection routes, and drone take-off and landing points. The artificial intelligence algorithms can accurately plan the routes of drones and vehicles in large-scale and complex wind farms.

8. The inspection method of the wind farm line inspection system based on the vehicle-mounted machine nest according to claim 2 is characterized in that: When the UAV is performing a mission, if it encounters an unknown obstacle on the inspection route, the UAV can avoid the obstacle on its own and return to the inspection route after bypassing the obstacle. At the same time, the UAV transmits the image and coordinates of the unknown obstacle to the onboard computer.

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