Unmanned aerial vehicle equipment for detecting evenness of expressway pavement and detection method of unmanned aerial vehicle equipment

Abstract

The invention discloses unmanned aerial vehicle equipment for highway pavement flatness detection and a detection method thereof, and relates to the technical field of pavement flatness detection device.The unmanned aerial vehicle equipment comprises a vehicle body and four vehicle arms installed on the two sides of the vehicle body, rotor wing mechanisms are installed at the far ends of the four vehicle arms correspondingly, and a protection frame is installed on the lower portion of the vehicle body; an image acquisition device and a protection mechanism are mounted on the protection frame; a system mainboard is arranged in the machine body, and a laser distance measuring sensor, an ultrasonic distance measuring sensor, a feature extraction module, a GNSS module, an inertia measurement module and a microcontroller are embedded in the machine body. A detection result is obtained through comprehensive analysis and judgment, the accuracy, comprehensiveness and reliability of detection data are improved, the undercarriage function, the rotor wing mechanism protection function and the image collection function are creatively integrated, the structure is exquisite and reasonable, the image collection device and the blades can be effectively protected, and the accidental damage situation of the unmanned aerial vehicle is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of road surface smoothness detection equipment, and in particular to an unmanned aerial vehicle device for high-speed road surface smoothness detection and a detection method thereof. Background Art

[0002] Highways should not only conduct quality control inspections during construction and quality assessment inspections for delivery and acceptance, but also conduct inspections and assessments on the long-term service of highways. The flatness of the road surface is one of the main technical indicators for evaluating the quality of the road surface. It is related to the safety and comfort of driving, the magnitude of the impact force on the road surface and the service life. The uneven road surface will increase the driving resistance and cause additional vibration to the vehicle. This vibration will cause driving bumps, affect the speed and safety of driving, and affect the stability of driving and the comfort of passengers. At the same time, the vibration will also exert impact force on the road surface, thereby aggravating the damage to the road surface and automobile parts and the wear of tires, and increasing the consumption of fuel. Moreover, for those located in water network areas, uneven roads will also accumulate rainwater and accelerate the damage of the road surface. In order to reduce the vibration impact force, increase the driving speed and increase the driving comfort and safety, the road surface should maintain a certain flatness. Due to the high driving speed of highways, the requirements for road surface flatness are higher.

[0003] In the prior art, the flatness of the road surface can be analyzed by making a road surface unevenness curve. The ordinate of the curve is the longitudinal displacement change value of the road surface, and the abscissa represents the length of the road. There are some shortcomings in using drones to detect the above two indicators: First, in terms of data acquisition accuracy, although the laser sensor is relatively accurate, in the face of some subtle texture changes on the road surface and special material roads, such as old and severely damaged asphalt roads or rough cement roads, the sensor may have data deviations, resulting in inaccurate measurement of the longitudinal displacement change value, which in turn affects the accuracy of the road surface unevenness curve. When performing data analysis, the analysis ability of some complex road surface diseases is insufficient, and it is difficult to provide a detailed and targeted road surface disease diagnosis report for the road maintenance department in a comprehensive and accurate manner; second, there are many vehicles passing through the expressway section at a high speed, and the safety of the drone itself needs to be improved. To this end, we provide a drone device for high-speed road surface flatness detection and a detection method thereof to solve the above problems. Summary of the invention

[0004] In view of the problems existing in the above-mentioned prior art, the present invention provides a UAV equipment and a detection method for detecting the flatness of a high-speed road surface. In addition to the relevant data of the road surface unevenness curve, the detection data is comprehensively analyzed by setting comparison data and combining the extracted image features, thereby improving the accuracy, comprehensiveness and reliability of the detection data. The landing gear function, rotor mechanism protection function and image acquisition function are creatively combined into one. Not only is the structure exquisite and reasonable, but it can also effectively protect the image acquisition device and blades, reduce accidental damage to the UAV, and extend the service life of the UAV.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts a drone device for high-speed road surface flatness detection, which includes a body and four arms installed on both sides of the body, and the far ends of the four arms are all installed with rotor mechanisms. A protective frame is installed at the lower part of the body, and an image acquisition device and a protective mechanism are installed on the protective frame; The above-mentioned body is provided with a system mainboard, on which a laser ranging sensor, an ultrasonic ranging sensor, a feature extraction module, a GNSS module, an inertial measurement module and a microcontroller are embedded, which are used for the collection, import, control, identification, analysis and data storage of flight data; Among them, the laser ranging sensor is used to obtain the longitudinal displacement change data of the highway road surface; The ultrasonic ranging sensor is used to obtain the flight altitude data of the UAV, which is used as the height comparison data of the longitudinal road surface shape data of the highway; The feature extraction module performs feature analysis on the images collected by the image acquisition device and passes the extracted features to the next module to identify debris other than the road surface on the highway; The inertial measurement module includes a gyroscope and an accelerometer, which are used to measure the angular velocity and linear acceleration of the drone. After processing and analysis, relevant data on the drone's flight attitude can be obtained. The gyroscope is a three-axis fiber optic gyroscope. The GNSS module is used to provide accurate location information of the drone and obtain displacement data while positioning, that is, the length data of the detected highway road surface; The microcontroller is used to control the operation of components in the device, and has a built-in wireless communication module with the functions of data analysis, storage, uploading and network learning; The above-mentioned protective mechanism is used to protect the rotor mechanism, which includes a telescopic assembly and a wing guard assembly. The bottom surface of the fuselage is provided with a storage compartment that cooperates with the telescopic assembly. The image acquisition device is installed on the telescopic assembly. The wing guard assembly covers the outside of the rotor mechanism to protect the rotor mechanism from collision.

[0006] As a further optimization of the above solution, the feature extraction module is a VGG16-Triplet module. Specifically, the Triplet module is introduced into VGG16. In the process of cropping, enhancing, identifying and extracting the collected images by the feature extraction module, the Triplet module interacts with information in three dimensions: channel dimension, height dimension and width dimension to ensure the accuracy of the final extracted information.

[0007] As a further optimization of the above scheme, the telescopic assembly includes a telescopic motor installed on the top surface of the accommodating bin, and the telescopic end of the motor is fixedly connected to the mounting platform. Both sides of the mounting platform are rotatably connected to support frames, and a wing guard assembly is installed at one end of the support frame away from the mounting platform. The support frame includes an H-shaped frame rotatably installed on the protective frame, and telescopic rods are provided at both ends of the H-shaped frame on one side close to the mounting platform, and wing guard assemblies are installed at both ends of the other side.

[0008] As a further optimization of the above scheme, the wing guard assembly includes a connecting frame, one end of the connecting frame is fixed on the H-shaped frame, and the other end is equipped with an arc-shaped wing guard plate, a high-pressure inflation nozzle is arranged in the middle part of the inner side of the arc-shaped wing guard plate, and a plurality of air outlet nozzles are opened on the outer side, and a hollow layer is arranged inside the arc-shaped wing guard plate, and an elastic air bag is arranged in the hollow layer, and the elastic air bag is sealed with the high-pressure inflation nozzle and the air outlet nozzle, and each of the air outlet nozzles is provided with a plug rod, and an air outlet groove is arranged at one end of the plug rod close to the air outlet nozzle, and a protective cover is arranged at the other end, and the bottom of the protective cover is fixed on the arc-shaped wing guard plate, and a pressure sensor is arranged in the hollow layer, and the output end of the pressure sensor is connected to the input end of the microcontroller.

[0009] As a further optimization of the above solution, a sealing rubber ring cooperating with the insertion rod is arranged in the air outlet nozzle.

[0010] As a further optimization of the above solution, the connecting portion between the H-shaped frame and the connecting frame is arc-shaped, and a landing support foot is provided in the middle of the outer side.

[0011] Based on the drone equipment for high-speed road surface flatness detection in the above scheme, the detection method includes the following steps: S1. Control the drone to fly to the height section to be tested, and hover and wait; S2, control the UAV to fly at the same horizontal altitude and start detection along the highway section, collect road image information through the image acquisition device, and judge the obstacle situation on the road based on the collected road image and feature extraction module; obtain the real-time spatial position and flight attitude of the UAV through the inertial measurement module and GNSS module, and obtain the height information of the UAV from the road through the laser ranging sensor and ultrasonic ranging sensor; S3, comprehensively determine the roughness of the road surface by combining the real-time spatial position of the drone, the flight attitude, the height information of the drone from the road surface, and the obstacles on the road surface; S4. Upload all data and test results to the data cloud.

[0012] As a further optimization of the above solution, the image acquisition device is a high-definition camera, and the rotor mechanism is composed of blades and a motor for driving the blades.

[0013] The drone device for detecting the flatness of a high-speed road surface of the present invention has the following beneficial effects: 1. The present invention provides a drone device for detecting the smoothness of a highway road surface and a detection method thereof. With the help of an advanced module integrated on the system mainboard, the longitudinal displacement value that grows synchronously with the detection length of the highway road surface can be accurately obtained during the detection process. With the help of an analysis library formed by a model constructed based on network learning and past detection data, the equipment can perform efficient curve drawing and deep curve result analysis on the collected data, and then accurately draw a conclusion on the detection of the smoothness of the highway road surface. Its intelligence level is excellent, and the detection results are not only accurate but also highly reliable. What is more outstanding is that the results can be presented immediately after the detection is completed, which greatly improves the detection efficiency and provides timely and accurate data support for highway road surface detection and management.

[0014] 2. The present invention relates to a drone device for detecting the smoothness of a highway road surface and a detection method thereof. During the detection operation, the device is equipped with an ultrasonic ranging sensor to accurately measure the distance between the drone and the road surface, and the data is used as the reference base data of the laser ranging sensor data. When there is a large deviation between the ranging values ​​of the two, the device will automatically retrieve the high-definition acquisition image corresponding to the deviation value, use the feature extraction technology of VGG16-Triplet, deeply extract the key features, and based on the extracted features, specifically analyze the root cause of the ranging difference, and integrate the analysis process and conclusions into a detailed analysis report to help the detection personnel accurately understand the detailed causes of the abnormal parts of the curve, thereby significantly improving the accuracy and reliability of the high-speed road surface smoothness detection results, further improving the reliability of the high-speed road surface smoothness detection results, and providing a powerful, detailed and comprehensive road surface diagnosis report for highway road surface detection.

[0015] 3. In the present invention, a drone device for detecting the flatness of a high-speed road surface and a detection method thereof, the protective mechanism as a whole can rotate around the connection between the H-shaped frame and the protective frame, which plays an important role in the landing and flight stages of the drone: 1) UAV landing stage: First, the wing assembly gradually rotates downward to act as a landing gear, reducing the risk of damage to the fuselage structure caused by landing impact, such as preventing the high-definition camera and other precision components of the drone from being displaced or damaged due to strong vibrations. It also increases the adaptability of the drone during landing, allowing it to land on different types of ground. Second, the telescopic assembly is stored in the storage compartment to ensure that the image acquisition device will not be damaged due to accidental collision with the ground during landing. For example, in a landing environment with obstacles, if the image acquisition device is exposed, it is easy to collide with flying debris on the ground, causing problems such as lens breakage and sensor failure. This design can effectively avoid such risks. 2) UAV take-off stage: First, the wing guard assembly rotates upward until it covers the outside of the rotor mechanism, which protects the blades and avoids flight loss of control accidents caused by blade damage. Its structural design can also guide the airflow to a certain extent, making the airflow flow more smoothly through the UAV body and reducing the impact of airflow turbulence on the flight attitude; second, the telescopic assembly is pushed out of the storage compartment to facilitate the operation of the image acquisition device; This structure creatively combines the landing gear function, rotor mechanism protection function and image acquisition function into one. Not only is the structure exquisite and reasonable, but it can also effectively protect the image acquisition device and extend its service life.

[0016] 4. The present invention provides a drone device for detecting the flatness of a high-speed road surface and a detection method thereof. A protective cover is cleverly added to the outer side of the arc-shaped wing guard plate, and an elastic airbag filled with high-pressure gas is cleverly integrated. When the rotating blades of the drone encounter unexpected collisions with obstacles or other emergencies, the protective cover will be the first to bear the impact. When the impact force is large, the plug will penetrate into the air outlet, causing the high-pressure gas to be ejected instantly through the air outlet groove thereon, generating a strong recoil force. This recoil force can effectively help the drone quickly move away from obstacles and prevent it from being continuously hit by obstacles, thereby protecting the drone in all directions and ensuring its safe operation in complex environments.

[0017] With reference to the following description and drawings, a specific embodiment of the present invention is disclosed in detail, indicating the manner in which the principle of the present invention can be adopted. It should be understood that the scope of the embodiment of the present invention is not limited thereby, and the embodiment of the present invention includes many changes, modifications and equivalents. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the three-dimensional structure of the present invention; Figure 2 A top view of the present invention; Figure 3 It is a front view of the present invention; Figure 4This is a schematic diagram of the structure of the wing assembly in the first embodiment of the present invention when it rotates downward to serve as a landing gear; Figure 5 is a control block diagram of the present invention; Figure 6 It is a schematic diagram of the process flow of the VGG16-Triplet module of the present invention for processing feature information; Figure 7 A top view of the UAV in the second embodiment of the present invention; Figure 8 It is a front view of the UAV in the second embodiment of the present invention; Fig. 9 for Figure 8 A in the enlarged view; Fig.10 It is a schematic diagram of the elastic airbag and its connection relationship in the second embodiment of the present invention.

[0019] In the figure: 1. body; 2. arm; 3. rotor mechanism; 4. protective frame; 5. image acquisition device; 6. telescopic assembly; 61. telescopic motor; 62. mounting platform; 63. support frame; 631. H-shaped frame; 632. telescopic rod; 7. wing guard assembly; 71. connecting frame; 72. arc-shaped wing guard plate; 73. high-pressure inflation nozzle; 74. outlet nozzle; 75. elastic airbag; 76. insertion rod; 77. protective cover; 78. sealing rubber ring; 79. pressure sensor; 8. landing support foot. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail below through the accompanying drawings and embodiments. However, it should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the scope of the present invention. Embodiment 1

[0021] Reference Figures 1 to 3 The present invention provides a technical solution: an unmanned aerial vehicle device for detecting the flatness of a high-speed road surface, comprising a body 1 and four arms 2 installed on both sides of the body 1, the four arms 2 are distributed in four directions of the front, back, left and right of the body 1, and the far ends of the four arms 2 are all equipped with rotor mechanisms 3 for driving the body 1 to fly. A protective frame 4 is installed at the lower part of the body 1, and an image acquisition device 5 and a protective mechanism for protecting the rotor mechanism 3 are installed on the protective frame 4.

[0022] Reference Figure 5 The body 1 is provided with a system mainboard, on which a laser ranging sensor, an ultrasonic ranging sensor, a feature extraction module, a GNSS module, an inertial measurement module and a microcontroller are embedded, which are used for the collection, import, control, identification, analysis and data storage of flight data; Among them, the laser ranging sensor is used to obtain the longitudinal displacement change data of the highway road surface, which is important data for drawing the road surface roughness curve; Reference Figure 6 The feature extraction module performs feature analysis on the image collected by the image acquisition device 5, and passes the extracted features to the next module to identify debris on the highway. The feature extraction module is a VGG16-Triplet module. Specifically, the Triplet module is introduced into VGG16 to perform information interaction on the three dimensions of channel dimension (C), height dimension (H), and width dimension (W) for the extracted image information to ensure the accuracy of the extracted information; The ultrasonic ranging sensor is used to obtain the flight altitude data of the drone, which is used as the height comparison data of the longitudinal road shape data of the highway road. By comparing the data with large differences, the angle of the aircraft 1 and the road surface characteristics corresponding to the data are comprehensively analyzed to analyze the reasons for the differences, and a report is formed and sent to the cloud to ensure the accuracy of the road surface unevenness curve; The inertial measurement module includes a gyroscope and an accelerometer, which are used to measure the angular velocity and linear acceleration of the drone. After processing and analysis, the relevant data of the drone's flight attitude can be obtained. The gyroscope is a three-axis fiber optic gyroscope with high detection accuracy. In addition, the setting of the accelerometer is also coordinated with the laser sensor. At this time, the accelerometer is used to provide the acceleration data of the drone in the XYZ three-axis direction. In addition, the data of the accelerometer and the laser ranging sensor are integrated with each other, which can also improve the data of the laser ranging sensor and improve the accuracy of the detection results; The GNSS module is used to provide accurate location information of the drone, and to obtain displacement data while positioning, that is, the length data of the detected high-speed road surface, which is another important data for drawing the road surface roughness curve. At the same time, the setting of the GNSS module also makes it convenient for operators to grasp its moving path and specific location at any time; The microcontroller is used to control the operation of the components in the equipment. It has two connection modes: Bluetooth connection and network connection. It has the functions of analyzing, storing, uploading data and network learning. Through network learning ability and combining previous detection experience, it establishes a corresponding feature database and a model of road surface roughness curve to establish an analysis library, saving the time of staff analysis after detection. It has a high degree of intelligence, and the data is uploaded to the cloud for easy access. Reference Figure 3 and 4The above-mentioned protective mechanism is used to protect the rotor mechanism 3, which includes a telescopic component 6 and a wing protection component 7. The bottom surface of the body 1 is provided with a storage bin that matches the telescopic component 6. The wing protection component 7 covers the outside of the rotor mechanism 3 to protect the rotor mechanism 3 from collision. The telescopic component 6 includes a telescopic motor 61 installed on the top surface of the storage bin, and its telescopic end is fixedly connected to the mounting platform 62. The image acquisition device 5 is a high-definition camera fixed on the mounting platform 62. Both sides of the mounting platform 62 are rotatably connected to a support frame 63. The end of the support frame 63 away from the mounting platform is equipped with the wing protection component 7. The support frame 63 includes an H-shaped frame 631 rotatably installed on the protective frame 4, and the two ends of the H-shaped frame 631 are close to the mounting platform 62. A telescopic rod 632 is provided, and wing guard assemblies 7 are installed at both ends of the other side. The wing guard assembly 7 includes a connecting frame 71, one end of the connecting frame 71 is fixed on the H-shaped frame 631, and the other end is installed with an arc-shaped wing guard plate 72. The telescopic assembly 6 can be moved in and out of the storage bin by the extension and contraction of the telescopic motor 61, and the rotation of the wing guard assembly 7 can be driven during the process. When the telescopic assembly 6 is lifted up and retracted into the storage bin, the wing guard assembly 7 is in a pulled-down state, which plays the role of a landing gear. Conversely, when the telescopic assembly 6 is pushed out of the storage bin, the wing guard assembly 7 rotates upward to protect the rotor mechanism 3. The connecting part between the H-shaped frame 631 and the connecting frame 71 is arc-shaped, and a landing support foot 8 is provided in the middle of the outer side to support the landing of the UAV.

[0023] Based on the drone equipment for high-speed road surface flatness detection provided in this embodiment, the specific detection method includes the following steps: S1. Control the drone to fly to the height section to be tested, and hover and wait; S2, control the UAV to fly at the same horizontal altitude, and start detection along the expressway section, collect road surface image information through the image acquisition device, and judge the obstacle situation on the road surface based on the collected road surface image and feature extraction module; obtain the real-time spatial position and flight attitude of the UAV through the inertial measurement module and the GNSS module, and obtain the height information of the UAV from the road surface through the laser ranging sensor and the ultrasonic ranging sensor, wherein the data detected by the laser ranging sensor is used as the displacement change data of the expressway road surface in the longitudinal direction, and the detection data of the ultrasonic ranging sensor is used as the comparison benchmark of the data, and the microcontroller integrates the flight attitude of the UAV, including the flight acceleration, angular velocity, and the above two sets of height data, to obtain more accurate height data, so that the subsequent road surface unevenness curve is more accurate, and a more accurate detection result is obtained; S3, the microcontroller establishes a feature database through network learning, and compares and analyzes it with the non-road materials detected by the feature extraction module to confirm the specific situation of the high-speed road obstacles. When there is a large difference between the data detected by the laser ranging sensor and the ultrasonic ranging sensor in S2, the microcontroller needs to combine the detection data at this location with the feature information extracted by the feature extraction module for rational analysis and generate a diagnostic analysis report; S4, the microcontroller establishes a model building and analysis library of the road surface roughness curve through program import and network learning, draws a road surface roughness curve in the model building and analysis library with the detected data, and analyzes the road surface flatness according to the curve diagram and the diagnosis analysis report in S3 to form a complete detection result; S5. Upload all data and test results to the data cloud.

[0024] Inspectors or other supervisors can obtain inspection data and results by logging into the cloud. The inspection results can provide a clearer picture of the smoothness of the highway surface, making it easier for the road maintenance department to conduct a comprehensive analysis of the highway surface conditions.

[0025] In the above steps, the take-off and landing process of the UAV is closely coordinated with the action of the protective mechanism. During flight, the wing assembly 7 rotates to and covers the periphery of the rotor mechanism 3, providing an all-round protective barrier for the blades. At this time, the telescopic assembly 6 is pushed out of the storage bin by the telescopic motor 61, and the image acquisition device 5 carried by it accurately collects road surface features in real time. When the UAV is ready to land, the telescopic motor 61 pulls the image acquisition device 5 on the mounting platform 62 back into the storage bin, and the image acquisition device 5 is properly protected. At the same time, the H-shaped frame 631 drives the wing assembly 7 to rotate, and the arc-shaped wing plate 72 is pulled down, and the landing support frame 8 on the connecting frame 71 connected thereto is firmly in contact with the landing bottom surface. At this time, the connecting frame 71 and the support frame 63 are cleverly transformed into a landing gear to ensure a smooth landing of the UAV.

[0026] Embodiment 2

[0027] Reference Figures 7 to 10 , which is different from the first embodiment, a high-pressure air-inflating nozzle 73 is provided in the middle of the inner side of the arc-shaped wing plate 72, and a plurality of air outlet nozzles 74 are provided on the outer side. A hollow layer is provided inside the arc-shaped wing plate 72, and an elastic air bag 75 is provided in the hollow layer. The elastic air bag 75 is sealed with the high-pressure air-inflating nozzle 73 and the air outlet nozzle 74. A plug rod 76 is provided in each air outlet nozzle 74. An air outlet groove is provided at one end of the plug rod 76 close to the air outlet nozzle 74, and a protective cover 77 is provided at the other end. The bottom of the protective cover 77 is fixed on the arc-shaped wing plate 72. A sealing rubber ring 78 is provided in the air outlet nozzle 74 to cooperate with the plug rod 76 to prevent gas leakage. A pressure sensor 79 is provided in the hollow layer, and the output end of the pressure sensor 79 is connected to the input end of the microcontroller.

[0028] During operation, the difference from the first embodiment is that a protective cover 77 is installed on the outer side of the arc-shaped wing plate 72. When the blades are accidentally hit by obstacles during rotation, the protective cover 77 will first bear the impact and be squeezed. When the impact force is large, the high-pressure gas will quickly leak out from the gas outlet groove. At this time, the elastic airbag 75 is like a balloon being deflated, and the high-pressure gas inside gushes out instantly, generating a strong recoil force. This recoil force pushes the drone back forcefully, making it quickly move away from obstacles, effectively preventing the drone from continuing to be hit by obstacles, thereby protecting the drone in all directions and ensuring its safe operation in complex environments.

[0029] After the high-pressure gas leaks out, the value of the pressure sensor 79 decreases rapidly, and the operator can quickly know the specific position of the blade that has been hit through the data change. After retracting the drone, the high-pressure gas can be refilled into the elastic airbag 75 through the high-pressure inflation nozzle 73 for subsequent use.

[0030] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions or improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A drone device for high-speed road surface smoothness detection, characterized in that: It comprises a machine body (1) and four machine arms (2) mounted on both sides of the machine body (1), the distal ends of the four machine arms (2) are all mounted with a rotor mechanism (3), a protective frame (4) is mounted at the lower part of the machine body (1), and an image acquisition device (5) and a protective mechanism are mounted on the protective frame (4); The body (1) is provided with a system main board, on which is embedded a laser ranging sensor for obtaining longitudinal displacement change data of the highway road surface, an ultrasonic ranging sensor for obtaining flight altitude data of the UAV, a feature extraction module for road surface information analysis, a GNSS module for providing accurate position and displacement data of the UAV, an inertial measurement module for obtaining flight attitude data of the UAV, and a microcontroller for controlling the operation of all components, including flight data collection, recognition, data analysis and storage, and a radio communication module is provided inside the microcontroller; The protective mechanism is used to protect the rotor mechanism (3), and comprises a telescopic assembly (6) and a wing guard assembly (7). The bottom surface of the body (1) is provided with a storage compartment that matches the telescopic assembly (6). The image acquisition device (5) is mounted on the telescopic assembly (6). The wing guard assembly (7) covers the outer side of the rotor mechanism (3) and is used to protect the rotor mechanism (3) from collision.

2. The unmanned aerial vehicle device for detecting the flatness of a high-speed road surface according to claim 1 is characterized in that: The inertial measurement module includes a gyroscope and an acceleration sensor, which are used to measure the angular velocity and linear acceleration of the drone. After processing and analysis, relevant data of the drone's flight attitude can be obtained. The gyroscope is a three-axis fiber optic gyroscope.

3. The unmanned aerial vehicle device for detecting the flatness of a high-speed road surface according to claim 2 is characterized in that: The GNSS module is used to provide accurate location information of the drone and obtain displacement data while positioning, that is, the length data of the detected highway road surface.

4. The unmanned aerial vehicle device for detecting the flatness of a high-speed road surface according to claim 3 is characterized in that: The feature extraction module is a VGG16-Triplet module. Specifically, the Triplet module is introduced into VGG16. During the process of cropping, enhancing, and identifying extraction pairs of the collected images, the Triplet module interacts with information in three dimensions: channel dimension, height dimension, and width dimension to ensure the accuracy of the final extracted information.

5. The unmanned aerial vehicle device for detecting the flatness of a high-speed road surface according to claim 4 is characterized in that: The telescopic assembly (6) comprises a telescopic motor (61) mounted on the top surface of the storage bin, the telescopic end of which is fixedly connected to a mounting platform (62), both sides of the mounting platform (62) are rotatably connected to support frames (63), one end of the support frame (63) away from the mounting platform is mounted with a wing guard assembly (7), the support frame (63) comprises an H-shaped frame (631) rotatably mounted on the protective frame (4), both ends of one side of the H-shaped frame (631) close to the mounting platform (62) are provided with telescopic rods (632), and both ends of the other side are mounted with wing guard assemblies (7).

6. The unmanned aerial vehicle device for detecting the flatness of a high-speed road surface according to claim 5 is characterized in that: The wing guard assembly (7) comprises a connecting frame (71), one end of the connecting frame (71) is fixed to the H-shaped frame (631), and the other end is provided with an arc-shaped wing guard plate (72), a high-pressure air nozzle (73) is arranged in the middle of the inner side of the arc-shaped wing guard plate (72), and a plurality of air outlet nozzles (74) are opened on the outer side, a hollow layer is arranged inside the arc-shaped wing guard plate (72), and an elastic air bag (75) is arranged in the hollow layer, and the elastic air bag (75) is sealed with the high-pressure air nozzle (73) and the air outlet nozzle (74), and each of the air outlet nozzles (74) is provided with a plug rod (76), and an air outlet groove is arranged at one end of the plug rod (76) close to the air outlet nozzle (74), and a protective cover (77) is arranged at the other end, and the bottom of the protective cover (77) is fixed to the arc-shaped wing guard plate (72), and a pressure sensor (79) is arranged in the hollow layer, and the output end of the pressure sensor (79) is connected to the input end of the microcontroller.

7. The unmanned aerial vehicle device for detecting the flatness of a high-speed road surface according to claim 6 is characterized in that: A sealing rubber ring (78) is provided inside the air outlet nozzle (74) and matches the insertion rod (76).

8. The unmanned aerial vehicle device for detecting the flatness of a highway road surface according to claim 7 is characterized in that: The connecting portion between the H-shaped frame (631) and the connecting frame (71) is arc-shaped, and a landing support foot (8) is provided in the middle of the outer side.

9. The unmanned aerial vehicle device for detecting the flatness of a high-speed road surface according to claim 8, characterized in that: The image acquisition device (5) is a high-definition camera, and the rotor mechanism (3) is composed of blades and a motor for driving the blades.

10. The detection method of the drone equipment for detecting the flatness of a high-speed road surface according to any one of claims 1 to 9 is characterized in that: The following steps are involved: S1. Control the drone to fly to the height section to be tested, hover and wait; S2, controlling the UAV to fly at the same horizontal altitude and start detection along the highway section, collecting road surface image information through the image acquisition device (5), judging the obstacle situation on the road surface based on the collected road surface image and the feature extraction module; obtaining the real-time spatial position and flight attitude of the UAV through the inertial measurement module and the GNSS module, and obtaining the height information of the UAV from the road surface through the laser ranging sensor and the ultrasonic ranging sensor; S3, comprehensively determine the roughness of the road surface by combining the real-time spatial position of the drone, the flight attitude, the height information of the drone from the road surface, and the obstacles on the road surface; S4. Upload all data and test results to the data cloud.

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