Urban rail transit protection zone risk source joint inspection system and method

Abstract

The present application relates to the technical field of urban rail transit risk monitoring, and discloses a kind of urban rail transit protection area risk source joint inspection system, comprising: vibration sensor is arranged in the inner wall of the tunnel of urban rail transit protection area, according to the tunnel direction, every certain distance is laid out a vibration sensor;Camera is arranged on the ground of urban rail transit protection area, according to the layout direction of vibration sensor, every certain distance is laid out a camera higher than ground, a camera corresponds with one or more vibration sensors;Unmanned aerial vehicle is arranged near the camera;Cloud platform is arranged in the inspection control room, and cloud platform is connected with vibration sensor, camera, unmanned aerial vehicle by wired communication or wireless communication mode respectively.The present application realizes the automatic inspection of urban rail transit, effectively reduces the risk of underground urban rail transit safety hidden trouble, and timely ensures the safe and stable operation of urban rail transit system.

Description

Technical Field

[0001] This invention relates to the field of urban rail transit risk monitoring technology, specifically to a joint inspection system and method for risk sources in urban rail transit protection zones. Background Technology

[0002] With the rapid pace of urbanization in my country and the ever-increasing urban population, urban transportation is under immense pressure. Traditional surface transportation struggles to meet the growing travel needs of the urban population, making urban rail transit a new mode of transportation that major cities are vigorously developing. While urban rail transit offers convenience and speed, significantly alleviating urban traffic problems, its underground structures are susceptible to deformation due to soil compression in complex geotechnical environments, leading to a series of safety hazards. Therefore, it is essential to consider the impact of heavy machinery operations within the urban rail transit protection zone on the tunnel's lifespan. As the social demand for urban rail transit inspections continues to rise, traditional manual inspections, primarily relying on paper records, suffer from problems such as untimely reporting, non-standard event recording, and inaccurate geographical location, resulting in low efficiency and effectiveness. Therefore, it is necessary to develop an automated inspection system specifically for urban rail transit protection. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention aims to provide a joint inspection system and method for risk sources in urban rail transit protection zones, enabling automatic inspection of urban rail transit, effectively reducing the risk of safety hazards in underground urban rail transit, and ensuring the safe and stable operation of urban rail transit systems in a timely manner.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A joint inspection system for risk sources in urban rail transit protection zones includes:

[0006] Vibration sensors: Multiple vibration sensors are evenly distributed along the tunnel direction on the inner wall of the tunnel within the urban rail transit protection zone to monitor vibration signals of the tunnel inner wall.

[0007] Cameras: Multiple cameras are evenly distributed along the layout of the vibration sensors at a height above the ground in the urban rail transit protection zone. Each camera corresponds to one or more vibration sensors and is used to capture images of risk sources within the detection range of the vibration sensors.

[0008] Drone: Located near the camera, one drone corresponds to multiple cameras, and is used to fly to the risk source to film the illegal operation when there is an obstruction between the camera and the risk source;

[0009] Cloud platform: Located in the inspection control room, it is connected to the vibration sensor, camera, and drone via wired or wireless communication. The cloud platform includes a first signal receiving module, a first judgment module, a first execution module, a second signal receiving module, a second judgment module, a second execution module, a third judgment module, and a third execution module. The first signal receiving module is used to acquire vibration sensor signals, and the first judgment module is used to determine whether there are risk sources above the tunnel based on the vibration sensor signals.

[0010] The first execution module is used to calculate the area range of the risk source when the risk source is confirmed, and to turn on the corresponding camera to capture the situation of the risk source based on the area range of the risk source.

[0011] The second signal receiving module is used to receive the images captured by the camera and process the captured images.

[0012] The second judgment module is used to determine whether there is an obstruction between the camera and the risk source based on the image captured by the camera;

[0013] The second execution module is used to control the drone corresponding to the camera to fly to the risk source and take pictures of the risk source when there is an obstruction between the camera and the risk source;

[0014] The third judgment module is used to determine whether there is any illegal operation at the risk source based on the images captured by the camera or the drone.

[0015] The third execution module is used to issue an alarm when there is a violation of regulations at the risk source, prompting the staff in the inspection control room to take appropriate action.

[0016] Furthermore, the vibration sensor is an optical fiber sensor.

[0017] Furthermore, the camera is installed at an unobstructed high position, and the camera is a multi-angle, all-around camera.

[0018] Furthermore, the drone is mounted on a nest, which is located below one of the cameras corresponding to the drone; the nest is equipped with a door and an automated gate control system connected to the door; the nest is also equipped with an automatic charging device, which is movably connected to the drone; the drone is equipped with a camera and is a multi-rotor drone.

[0019] An inspection method based on the joint inspection system for risk sources in the urban rail transit protection zone includes:

[0020] S01. Deploy vibration sensors, cameras, and drones:

[0021] S02. Acquire vibration sensor signal.

[0022] S03. Determine if there are any risk sources above the tunnel by using vibration sensor signals:

[0023] S04. When it is confirmed that there is a risk source above the tunnel, calculate the area range of the risk source, and according to the area range of the risk source, turn on the corresponding camera to take pictures of the risk source.

[0024] S05. Receive the image captured by the camera and process the captured image;

[0025] S06. Determine whether there is an obstruction between the camera and the risk source;

[0026] S07. When there is an obstruction between the camera and the risk source, control the drone corresponding to the camera to fly to the risk source, take a picture of the risk source and proceed to step S08; when there is no obstruction between the camera and the risk source, proceed directly to step S08 after completing step S06.

[0027] S08. Determine whether there is any illegal operation at the risk source based on the images captured by the camera or the drone;

[0028] S09. When there is a violation of regulations at the risk source, an alarm is issued to prompt the staff in the inspection control room to take appropriate measures.

[0029] The measures include: the cloud platform sending instructions to the drone to control it to fly to the illegal work site and stop the violator by warning sound or light; or the drone or camera capturing the image of the violator and transmitting it to the cloud platform, where image recognition technology is used to confirm the violation and identify the violator.

[0030] Furthermore, the method for deploying the vibration sensors is as follows: A vibration sensor is deployed at regular intervals according to the tunnel's orientation, ensuring that the vibration sensor can detect and locate external vibration signals. The method for deploying the cameras is as follows: On the ground within the urban rail transit protection zone, a camera higher than the ground is deployed at regular intervals along the tunnel wall, according to the orientation of the vibration sensors. Each camera corresponds to one or more vibration sensors. The camera installation points are unobstructed high locations, away from vegetation areas. The method for deploying the drones is as follows: A drone pod is deployed below the camera, with one drone corresponding to multiple cameras. The pod is located below one of the cameras corresponding to the drone.

[0031] Furthermore, the step of determining whether there is a risk source above the tunnel by using vibration sensor signals is as follows: establish a database of illegal operation signals in the cloud platform. When a vibration sensor signal is received, the cloud platform will automatically compare the wavelengths to determine whether there is a risk source.

[0032] Furthermore, the step of calculating the regional range of the risk source is as follows:

[0033] The cloud platform records the three-dimensional coordinates A of each vibration sensor. i and the distance D between the vibration sensor and the ground. i Where i is the number of the vibration sensor;

[0034] When a risk source is generated, the vibration sensor receives the vibration information generated by the risk source, and the cloud platform obtains the three-dimensional coordinates A of the vibration sensor. i The distance D between the vibration sensor and the ground i And based on the vibration information, the distance S between the vibration sensor and the risk source is obtained. i The horizontal distance X between the risk source and the vibration sensor is calculated using the following formula. i The formula is: X i 2 =S i 2 -D i 2 Based on the horizontal distance X between the risk source and the vibration sensor i and the three-dimensional coordinates A of the vibration sensor i The geographical scope of the risk source is determined.

[0035] Furthermore,

[0036] The step of determining whether there is an obstruction between the camera and the risk source is as follows: when the area range of the risk source is calculated, the camera corresponding to the vibration sensor is turned on, and the line-of-sight analysis is used to determine whether there is an obstruction between the camera and the risk source. If there is, the feedback is sent to the drone through the cloud platform.

[0037] S07 also includes: after receiving feedback, the drone plans a route based on the location information of the risk source and the drone nest, and flies to the risk source with the assistance of the global positioning system to take pictures.

[0038] Furthermore,

[0039] The steps for determining whether there are violations at the risk source are as follows: The cloud platform constructs a sample library of machinery and equipment involved in violations, uses deep learning to train and verify a verification model, and after receiving images captured by cameras or drones, the cloud platform identifies the risk source using the verification model.

[0040] Step S09 further includes: after identifying illegal operations at the risk source, accurately locating the risk source based on the principle of photogrammetry.

[0041] The beneficial effects of this invention are as follows:

[0042] This invention monitors vibration within tunnels by deploying vibration sensors, enabling rapid detection of potential safety risks, such as equipment malfunctions, and facilitating timely intervention. Utilizing a cloud platform to control ground-based high-position cameras and drones allows for efficient monitoring and remote control of these risk sources, improving monitoring accuracy and real-time performance. The cloud platform also enables automated analysis and judgment of images captured by cameras and drones, quickly identifying any violations and reducing the burden of manual judgment, thus improving efficiency and accuracy. Once the cloud platform detects violations at a risk source, it immediately issues an alarm to notify staff for action, achieving rapid response and early warning, and reducing the likelihood of accidents. This invention effectively improves the safety and management efficiency of underground urban rail transit systems, reduces the probability of safety risks, and ensures the safety of passengers and staff. Attached Figure Description

[0043] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0044] Figure 1 This is a flowchart illustrating the workflow of a joint inspection system for risk sources in urban rail transit protection zones according to the present invention.

[0045] Figure 2This is a schematic diagram illustrating the working principle of a joint inspection system for risk sources in urban rail transit protection zones according to the present invention.

[0046] Figure 3 This is a structural diagram of a joint inspection system for risk sources in urban rail transit protection zones according to the present invention. Detailed Implementation

[0047] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0048] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0049] It should be noted that the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, such as a process, method, system, product, or device that includes a series of steps or units, which is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0050] A joint inspection system for risk sources in urban rail transit protection zones, such as Figure 1 , Figure 2 and Figure 3 As shown, it includes: a vibration sensor, a camera, a drone, and a cloud platform. The vibration sensor, camera, and drone are all connected to the cloud platform via wired or wireless communication.

[0051] (1) Vibration sensor: Installed on the inner wall of the tunnel in the urban rail transit protection zone, vibration sensors are buried along the top of the urban rail transit tunnel according to the tunnel direction, and a vibration sensor is deployed at a certain distance to receive vibration signals generated by the risk source above the tunnel.

[0052] The vibration sensor uses a fiber optic sensor, with an optimal detection range of L. This optimal range ensures the sensor can detect and locate external vibration signals. One fiber optic sensor is deployed every L, and the three-dimensional coordinates (X, Y, F, Z) of each sensor are recorded. 光纤传感器 Y 光纤传感器 Z 光纤传感器The fiber optic sensor receives a vibration signal, acquires its position, and calculates the distance S between the sensor and the location of the violation. This information is based on the known distance D between the sensor and the ground. i Calculate the horizontal distance X between the violation point and the sensor. i For: X i 2 =S i 2 -D i 2 Where i is the vibration sensor number. Based on this, the approximate horizontal distance between the violation point and the fiber optic sensor can be determined.

[0053] (2) Cameras: Set on the ground in the urban rail transit protection zone. According to the layout of the vibration sensors, a camera higher than the ground is set at regular intervals. Each camera corresponds to one or more vibration sensors and is used to capture the situation of the risk source. The distance between cameras can be 500 meters.

[0054] The camera is installed at an unobstructed high position and is a multi-angle, all-around camera.

[0055] When setting up the equipment, environmental changes such as vegetation should be taken into account to ensure long-term stable shooting.

[0056] Based on the three-dimensional coordinates of the work site, the camera is used to observe the risk source. The three-dimensional coordinates of the camera (X) are known. 高位摄像头 Y 高位摄像头 Z 高位摄像头 The approximate horizontal range of the fiber optic sensor and the distance between the violation point and the point of operation is used to ensure there are no blind spots by establishing a straight line between the two points.

[0057] (3) Drones: set up near the camera, used to fly to the risk source to take pictures of illegal operations when there are obstructions between the camera and the risk source;

[0058] The drone is mounted on a nest located below a camera. The nest is equipped with a door and an automated gate control system connected to the door. The nest also has an automatic charging device connected to the drone. The drone is a multi-rotor drone equipped with a camera. The drone nest (X) is positioned below a high-level camera. 机巢， Y 机巢 Z 机巢 The specific structure of the drone is as follows:

[0059] 1) Configure an automated gate control system that automatically turns on when the drone returns to its nest and automatically turns off when it takes off, protecting the drone from external interference.

[0060] 2) Equipped with an automatic charging function, the drone can automatically dock with the charger when it lands.

[0061] 3) Use a precast concrete base or gravity base with good waterproof performance.

[0062] 4) Equip with a multi-rotor drone with a camera, and select a location that facilitates the take-off and landing of the drone.

[0063] Drone flight path settings:

[0064] When unauthorized operations occur, the camera's line-of-sight analysis of the unauthorized operation site reveals obstructions, which are then relayed to the drone. Upon receiving this feedback, the drone plans its route based on the location of the unauthorized operation site and its drone nest. The drone nest is installed near the camera, and the camera's images of the protected area can identify blind spots. Therefore, the drone's flight path within the protected area can be planned for both flight and blind spot monitoring.

[0065] (4) Cloud platform: Used to receive signals from vibration sensor units and determine whether there is a risk source based on the signals; if there is a risk source, control the camera corresponding to the vibration sensor that has received the risk source signal to turn on and take pictures of the risk source; receive the images taken by the camera and process the images to determine whether there is an obstruction between the camera and the risk source; if there is an obstruction between the camera and the risk source, control the drone corresponding to the camera to fly to the risk source and take pictures of the risk source; analyze the risk source situation based on the images taken by the camera or drone, and if there is a violation of regulations, issue an alarm to prompt the staff in the inspection control room to take appropriate action.

[0066] Specifically, the cloud platform is located in the inspection control room and is connected to the vibration sensors, cameras, and drones via wired or wireless communication. The cloud platform includes a first signal receiving module, a first judgment module, a first execution module, a second signal receiving module, a second judgment module, a second execution module, a third judgment module, and a third execution module. The first signal receiving module is used to acquire vibration sensor signals.

[0067] The first judgment module is used to determine whether there are risk sources above the tunnel by using vibration sensor signals;

[0068] The first execution module is used to calculate the area of ​​the risk source when a risk source is confirmed, and to turn on the corresponding camera to capture the situation of the risk source based on the area of ​​the risk source.

[0069] The second signal receiving module is used to receive images captured by the camera and process the captured images.

[0070] The second judgment module is used to determine whether there is an obstruction between the camera and the risk source based on the image captured by the camera;

[0071] The second execution module is used to control the drone corresponding to the camera to fly to the risk source and take pictures of the risk source when there is an obstruction between the camera and the risk source.

[0072] The third judgment module is used to determine whether there are any violations of regulations at the risk source based on images captured by cameras or drones.

[0073] The third execution module is used to issue an alarm when there is a violation of regulations at the risk source, prompting the staff in the inspection control room to take appropriate action.

[0074] The cloud platform is responsible for data processing and management of each inspection unit, as well as the linkage between each inspection unit. It provides centralized and unified management of each risk source inspection unit, including functions such as data collection, data storage, data processing, risk source identification, and risk source location.

[0075] An inspection method based on a joint inspection system for risk sources in urban rail transit protection zones includes the following steps:

[0076] S01. Deploy vibration sensors, cameras, and drones:

[0077] Vibration sensor deployment: Based on the tunnel's orientation, vibration sensors are deployed at regular intervals to ensure they can detect and locate external vibration signals. The optimal sensor layout is calculated using intelligent algorithms based on the tunnel's geological conditions, curvature, traffic flow, and environmental noise, ensuring best monitoring performance under various conditions. This adaptive layout design aims to improve the sensitivity and accuracy of the fiber optic sensing system while reducing monitoring blind spots caused by environmental changes.

[0078] Camera deployment: On the ground in the urban rail transit protection zone, a camera higher than the ground is deployed at regular intervals according to the deployment direction of the vibration sensors. One camera corresponds to one or more vibration sensors. The camera installation points are unobstructed high locations and far away from vegetation areas.

[0079] Drone deployment: Deploy drone nests below the camera location.

[0080] S02, Acquire vibration sensor signal;

[0081] S03. Determine whether there are risk sources above the tunnel by using vibration sensor signals;

[0082] The cloud platform system processes vibration signals and establishes a database of violation operation signals in the cloud platform. When a vibration sensor signal is received, the cloud platform will automatically compare the wavelengths to determine whether there is a risk source.

[0083] S04. When a risk source is confirmed, calculate the area of ​​the risk source and, based on the area of ​​the risk source, turn on the corresponding camera to capture the situation of the risk source.

[0084] Once a risk source is identified, the area of ​​the risk source is determined using vibration sensors, specifically:

[0085] The cloud platform records the three-dimensional coordinates A of each vibration sensor, as well as the distance D between the vibration sensor and the ground. i Where i is the number of the vibration sensor;

[0086] When a risk source is generated, the vibration sensor receives the vibration information generated by the risk source, and the cloud platform obtains the three-dimensional coordinates A of the vibration sensor. i The distance D between the vibration sensor and the ground i And based on the vibration information, calculate the distance S between the vibration sensor and the risk source. i The horizontal distance X between the risk source and the vibration sensor is calculated using the following formula. i The formula is: X i 2 =S i 2 -D i 2 Based on the horizontal distance X between the risk source and the vibration sensor i and the three-dimensional coordinates A of the vibration sensor i Determine the geographical scope of the risk source;

[0087] The cloud platform transmits the identified risk source area to nearby cameras, which then adjust their focus and orientation based on the information received from the cloud platform to capture images of the risk source location.

[0088] S05. Receive images captured by the camera and process the captured images:

[0089] The camera transmits the captured images to the cloud platform via a data transmission link, and the cloud platform uses image processing algorithms to accurately identify and locate the sources of risk.

[0090] S06. Determine if there are any obstructions between the camera and the risk source:

[0091] S07. When there is an obstruction between the camera and the risk source, control the drone corresponding to the camera to fly to the risk source, take a picture of the risk source and proceed to step S08; when there is no obstruction between the camera and the risk source, proceed directly to step S08 after completing step S06.

[0092] Once the area of ​​the risk source is determined, the system selects the camera closest to the risk source based on the location of the fiber optic sensor, activates the camera corresponding to the vibration sensor, and uses line-of-sight analysis to determine if there is any obstruction between the camera and the risk source. If there is no obstruction, the image captured by the camera is directly transmitted to the cloud platform for analysis. If there is obstruction, the cloud platform provides feedback to the drone. After receiving the feedback, the drone plans a route based on the risk source and the location of the drone nest, and flies to the risk source with the assistance of the Global Positioning System to take pictures.

[0093] Fiber optic sensors in underground tunnels can locate nearby cameras based on their position relative to the ground, and adjust the camera's shooting direction according to the protected area's orientation.

[0094] Through line-of-sight analysis, if the high-position camera is obstructed or has other abnormalities during the shooting process, it will report to the cloud platform system. The cloud platform system will then notify the drone in the nest to take off and fly to the risk source location determined by the fiber optic inspection unit with the assistance of the global positioning system to take pictures. The captured images will also be transmitted to the cloud platform system for detailed identification and location of the risk source.

[0095] S08. Determine whether there are any violations of regulations at the risk source based on images captured by cameras or drones.

[0096] S09. When there is a violation of regulations at the risk source, an alarm will be issued to prompt the staff in the inspection control room to take appropriate action.

[0097] The cloud platform constructs a sample library of machinery and equipment operating in violation of regulations, and uses deep learning to train and verify a verification model. After receiving images taken by cameras or drones, the cloud platform identifies risk sources through the verification model. Once a violation is identified at a risk source, the risk source is precisely located based on the principles of photogrammetry. The cloud platform system then notifies management personnel to take measures to address the violation at the risk source.

[0098] The measures taken include: once a violation is confirmed, the cloud platform sends a notification to the drone pod, which then flies to the location of the risk source and uses its onboard image sensor to capture a clear image of the risk source location, while simultaneously stopping the operator through warning sounds or lights; or, the drone or camera captures an image of the violator and transmits it to the cloud platform, where image recognition technology is implemented to confirm the violation and identify potential violators.

[0099] For those skilled in the art, various other corresponding changes and modifications can be made based on the technical solutions and concepts described above, and all such changes and modifications should fall within the protection scope of the claims of this invention.

Claims

1. A joint inspection system for risk sources in urban rail transit protection zones, characterized in that, include: Vibration sensors: Multiple vibration sensors are evenly distributed along the tunnel direction on the inner wall of the tunnel within the urban rail transit protection zone to monitor vibration signals of the tunnel inner wall. Cameras: Multiple cameras are evenly distributed along the layout of the vibration sensors at a height above the ground in the urban rail transit protection zone. Each camera corresponds to one or more vibration sensors and is used to capture images of risk sources within the detection range of the vibration sensors. Drone: Located near the camera, one drone corresponds to multiple cameras, and is used to fly to the risk source to film the illegal operation when there is an obstruction between the camera and the risk source; Cloud platform: Located in the inspection control room, it is connected to the vibration sensor, camera, and drone via wired or wireless communication. The cloud platform includes a first signal receiving module, a first judgment module, a first execution module, a second signal receiving module, a second judgment module, a second execution module, a third judgment module, and a third execution module. The first signal receiving module is used to acquire vibration sensor signals; The first judgment module is used to determine whether there is a risk source above the tunnel based on the vibration sensor signal; The first execution module is used to calculate the area range of the risk source when the risk source is confirmed, and to turn on the corresponding camera to capture the situation of the risk source based on the area range of the risk source. The second signal receiving module is used to receive the images captured by the camera and process the captured images; The second judgment module is used to determine whether there is an obstruction between the camera and the risk source based on the image captured by the camera; The second execution module is used to control the drone corresponding to the camera to fly to the risk source and take pictures of the risk source when there is an obstruction between the camera and the risk source; The third judgment module is used to determine whether there is any illegal operation at the risk source based on the images captured by the camera or the drone. The third execution module is used to issue an alarm when there is a violation of regulations at the risk source, prompting the staff in the inspection control room to take appropriate action.

2. The joint inspection system for risk sources in urban rail transit protection zones according to claim 1, characterized in that, The vibration sensor is an optical fiber sensor.

3. The joint inspection system for risk sources in urban rail transit protection zones according to claim 1, characterized in that, The camera is installed at an unobstructed high position and is a multi-angle, all-around camera.

4. The joint inspection system for risk sources in urban rail transit protection zones according to claim 1, characterized in that, The drone is mounted on a nest, which is located below one of the cameras corresponding to the drone; the nest is equipped with a door and an automated gate control system connected to the door; the nest is also equipped with an automatic charging device, which is movably connected to the drone, and the drone is equipped with a camera.

5. An inspection method based on the joint inspection system for risk sources in urban rail transit protection zones according to any one of claims 1-4, characterized in that, S01. Deploy vibration sensors, cameras, and drones; S02, Acquire vibration sensor signal; S03. Determine whether there are risk sources above the tunnel by using vibration sensor signals; S04. When it is confirmed that there is a risk source above the tunnel, calculate the area range of the risk source, and according to the area range of the risk source, turn on the corresponding camera to take pictures of the risk source. S05. Receive the image captured by the camera and process the captured image; S06. Determine whether there is an obstruction between the camera and the risk source; S07. When there is an obstruction between the camera and the risk source, control the drone corresponding to the camera to fly to the risk source, take a picture of the risk source, and proceed to step S08; when there is no obstruction between the camera and the risk source, proceed directly to step S08 after completing step S06. S08. Determine whether there is any illegal operation at the risk source based on the images captured by the camera or the drone; S09. When there is a violation of regulations at the risk source, an alarm is issued to prompt the staff in the inspection control room to take appropriate measures. The measures include: the cloud platform sending instructions to the drone to control it to fly to the illegal work site and stop the violator by warning sound or light; or the drone or camera capturing the image of the violator and transmitting it to the cloud platform, where image recognition technology is used to confirm the violation and identify the violator.

6. The inspection method according to claim 5, characterized in that, The vibration sensor deployment method is as follows: A vibration sensor is deployed at regular intervals along the tunnel's orientation on the tunnel wall, ensuring that the vibration sensor can detect and locate external vibration signals. The camera deployment method is as follows: A camera, positioned above ground level, is deployed at regular intervals along the vibration sensor's orientation on the ground within the urban rail transit protection zone. Each camera corresponds to one or more vibration sensors. The camera is installed at an unobstructed, elevated location, away from vegetation. The drone deployment method is as follows: A drone nest is deployed below each camera, with one drone corresponding to multiple cameras. The nest is located below one of the cameras corresponding to the drone.

7. The inspection method according to claim 5, characterized in that, The step of determining whether there is a risk source above the tunnel by using vibration sensor signals is as follows: establish a database of illegal operation signals in the cloud platform. When a vibration sensor signal is received, the cloud platform will automatically compare the wavelengths to determine whether there is a risk source.

8. The inspection method according to claim 5, characterized in that, The steps for calculating the geographical extent of the risk source are as follows: The cloud platform records the three-dimensional coordinates A of each vibration sensor. i and the distance D between the vibration sensor and the ground. i Where i is the number of the vibration sensor; When a risk source is generated, the vibration sensor receives the vibration information generated by the risk source, and the cloud platform obtains the three-dimensional coordinates A of the vibration sensor. i The distance D between the vibration sensor and the ground i And based on the vibration information, the distance S between the vibration sensor and the risk source is obtained. i The horizontal distance X between the risk source and the vibration sensor is calculated using the following formula. i The formula is: X i 2 =S i 2 -D i 2 Based on the horizontal distance X between the risk source and the vibration sensor i and the three-dimensional coordinates A of the vibration sensor i The geographical scope of the risk source is determined.

9. The inspection method according to claim 8, characterized in that, The step of determining whether there is an obstruction between the camera and the risk source is as follows: when the area range of the risk source is calculated, the camera corresponding to the vibration sensor is turned on, and the line-of-sight analysis is used to determine whether there is an obstruction between the camera and the risk source. If there is, the feedback is sent to the drone through the cloud platform. S07 also includes: after receiving feedback, the drone plans a route based on the location information of the risk source and the drone nest, and flies to the risk source with the assistance of the global positioning system to take pictures.

10. The inspection method according to claim 5, characterized in that, The steps for determining whether there are violations at the risk source are as follows: The cloud platform constructs a sample library of machinery and equipment involved in violations, uses deep learning to train and verify a verification model, and after receiving images captured by cameras or drones, the cloud platform identifies the risk source using the verification model. Step S09 further includes: after identifying illegal operations at the risk source, accurately locating the risk source based on the principle of photogrammetry.

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