Tunnel safety detection method based on unmanned aerial vehicle communication and charging facility integration

Abstract

The invention provides a tunnel safety detection method based on unmanned aerial vehicle communication and charging facility integration, and relates to the technical field of tunnel safety detection. According to the method, a signal relay module, a wireless charging module and a telescopic take-off and landing platform are integrated through integrated equipment and are embedded into the side wall of a tunnel for deployment, and the problems that a traditional split type device is unstable in signal, insufficient in endurance, large in occupied space and the like are solved. After receiving the inspection task issued by the central management platform, the unmanned aerial vehicle flies along a preset path and collects environment data in real time; when the electric quantity is insufficient, the platform dynamically dispatches the nearest integrated equipment, the unmanned aerial vehicle accurately lands to the telescopic take-off and landing platform through laser radar and visual identification, the wireless charging module starts charging, and meanwhile the signal relay module returns data. After charging is completed, the platform generates a new task instruction, and the unmanned aerial vehicle continues to execute remaining inspection.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel safety detection, and in particular to a tunnel safety detection method based on the integration of UAV communication and charging facilities. Background Art

[0002] Traditional tunnel safety detection relies on split signal relay stations and independent charging devices, and there are the following problems: First, unstable signal coverage: satellite signals are blocked in the tunnel, and the UAV communication link is easily interrupted, resulting in the failure of detecting data backhaul; Second, insufficient endurance: in the long-distance tunnel environment, it is difficult for a UAV to cover the whole journey in a single flight, and it is necessary to frequently return or manually replace the battery, with low detection efficiency; Third, space occupation and electromagnetic interference: the split devices are installed dispersedly, occupying the tunnel space, and when the relay module and the charging device coexist in close proximity, electromagnetic interference causes the communication quality to decline or the charging efficiency to decrease; Fourth, high maintenance cost: the independent deployment of multiple devices requires frequent maintenance, and manual intervention affects the normal operation of the tunnel.

[0003] Although existing technologies have tried to apply UAVs to tunnel inspection, limited by the above problems, it is still difficult to achieve efficient, continuous, and autonomous safety detection. Summary of the Invention

[0004] In view of the above problems existing in the prior art, the present invention proposes a tunnel safety detection method based on the integration of UAV communication and charging facilities, including: Step S1: The UAV receives the inspection task instruction sent by the central management platform, flies along the tunnel based on the preset path, and collects environmental data in real time; Step S2: The UAV monitors the remaining power. When the remaining power is lower than the preset power threshold, a charging request signal is generated and sent to the central management platform; Step S3: The central management platform determines the location information of the nearest integrated device based on the charging request signal and the tunnel topology map, and sends it to the UAV. The integrated device includes a signal relay module, a wireless charging module, and a telescopic take-off and landing platform; Step S4: The UAV scans the positioning marker points of the integrated device according to the location information, calculates the landing deviation, and adjusts the flight attitude before landing on the telescopic take-off and landing platform; Step S5: The wireless charging module starts charging based on the landing completion signal. At the same time, the signal relay module receives the environmental data and backhauls it to the central management platform; Step S6: The central management platform monitors the charging completion status, generates a new inspection instruction and sends it to the UAV, and the UAV continues to execute the remaining tasks.

[0005] In some implementation manners, in step S5, Before the wireless charging module starts the charging operation, it scans the surface area of the telescopic takeoff and landing platform through the foreign object detection sensor to obtain the surface area image data; The foreign object detection sensor performs feature analysis on the surface area image data. If the foreign object contour feature is detected, a foreign object warning signal is generated and sent to the central management platform; Based on the foreign object warning signal, the central management platform suspends the start instruction of the wireless charging module and sends a maintenance request containing the foreign object position coordinates and the surface area image data to the maintenance terminal; After receiving the maintenance request, the maintenance terminal triggers the automatic cleaning robotic arm or the manual cleaning process. After clearing the foreign object, a cleaning completion signal is generated; After receiving the cleaning completion signal, the central management platform resends the charging start instruction to the wireless charging module and continues to execute the charging operation.

[0006] In some implementation manners, in step S3, The central management platform filters multiple candidate integrated devices with a distance from the path node less than the preset distance threshold from the tunnel topology map according to the current flight path of the unmanned aerial vehicle; Based on the real-time communication signal strength value and the charging queue waiting duration of the candidate integrated devices, the comprehensive priority score of each candidate integrated device is calculated; The target integrated device with the highest comprehensive priority score is selected, its position coordinates and communication frequency band information are extracted, and encapsulated as a navigation instruction and sent to the unmanned aerial vehicle; After receiving the navigation instruction, the unmanned aerial vehicle updates the flight path based on the position coordinates and switches to the communication frequency band to establish a communication connection with the target integrated device.

[0007] In some implementation manners, in step S5, After taking over the communication link of the unmanned aerial vehicle, the signal relay module real-time collects the signal strength values of adjacent integrated devices and generates a signal strength distribution map; If the signal strength value of the current communication link is lower than the preset strength threshold, the adjacent integrated device with the highest signal strength value is selected from the signal strength distribution map as the switching target; The communication link of the unmanned aerial vehicle is switched to the communication frequency band of the switching target, and the environmental data is continuously transmitted to the central management platform through the switched communication link; The central management platform records the communication link switching event, updates the communication status mark of the corresponding node in the tunnel topology map, and synchronizes the updated map to all integrated devices.

[0008] In some implementation manners, in step S4, After receiving the landing request signal of the unmanned aerial vehicle, the telescopic takeoff and landing platform drives the platform surface to unfold from the folded state to the horizontal working state through the electric push rod; After the platform surface is deployed, the deployment mechanism is locked by electromagnetic pins, and a platform ready signal is generated and sent to the drone; After the drone receives the platform ready signal, it scans the positioning marker points on the platform surface through lidar to obtain the three-dimensional coordinate data of the marker points; Based on the deviation value between the three-dimensional coordinate data and the preset standard coordinates, calculate the flight attitude adjustment parameters, and control the pitch angle and roll angle of the drone until the plane deviation between the power receiving coil and the transmitting coil is less than the tolerance threshold, and then complete the landing.

[0009] In some implementation manners, in step S1, During the flight of the drone, it receives the tunnel obstacle coordinate data pushed by the central management platform in real time through the signal relay module; If the on-board obstacle avoidance sensor of the drone detects that the obstacle ahead conflicts with the current flight path, an obstacle avoidance path planning request is generated, and the obstacle size and position information are attached and sent to the central management platform; Based on the obstacle information and combined with the tunnel structure model data, the central management platform generates an obstacle avoidance flight path including detour waypoints and speed constraints; After receiving the obstacle avoidance flight path, the drone adjusts the thrust distribution of the thrusters, bypasses the obstacle according to the waypoints and speed constraints, and resumes the original preset path to continue the inspection after bypassing.

[0010] In some implementation manners, in step S5, After the wireless charging module aligns the magnetic resonance coupling coil with the power receiving coil of the drone, it starts to generate charging energy by an alternating magnetic field; During the charging process, the battery temperature and charging voltage data of the drone are collected in real time through the temperature sensor and the voltage sampling circuit; If the battery temperature exceeds the safety threshold or the charging voltage fluctuation exceeds the preset voltage range, the output of the alternating magnetic field is cut off, and a charging fault code including the fault type and timestamp is generated; After receiving the charging fault code, the central management platform schedules the nearest standby integrated device to take over the charging task according to the fault type, or sends a maintenance instruction including the fault type to the maintenance terminal.

[0011] In some implementation manners, in step S6, After the drone finishes charging, the central management platform extracts the coordinate set and priority tags of the remaining uninspected areas; Based on the Euclidean distance between the current position of the drone and each uninspected area, the area priority weight, and the path complexity factor, calculate the optimal task assignment order; Package the optimal task assignment order into a new inspection instruction including a waypoint sequence and a task time window, and send it to the drone; After the UAV analyzes the new inspection instructions, it updates the path planning of the on-board navigation system and executes the remaining inspection tasks according to the task time window.

[0012] In some implementation manners, in step S3, The integrated device collects the temperature, humidity and harmful gas concentration data in the tunnel in real time through the environment perception unit, and generates an environment monitoring data set; The environment perception unit uploads the environment monitoring data set to the central management platform through the signal relay module; The central management platform statistically analyzes the environment monitoring data set. If it detects that the temperature exceeds the safety threshold or the harmful gas concentration exceeds the standard, it marks the corresponding coordinates as abnormal areas; Add the coordinates of the abnormal area to the preset path of the subsequent inspection task, and collect the environment data of the abnormal area.

[0013] In some implementation manners, in step S5, The integrated device discharges the heat generated during the operation of the wireless charging module and the signal relay module to the outside of the tunnel through a heat dissipation system composed of a heat dissipation fan and a diversion channel; The heat dissipation system monitors the internal temperature of the integrated device in real time through a temperature sensor, and dynamically adjusts the rotation speed of the heat dissipation fan according to the temperature value; If the internal temperature continuously exceeds the set temperature threshold, reduce the output power of the wireless charging module, and generate an overheat alarm signal including the device number and the temperature value; After receiving the overheat alarm signal, the central management platform schedules the adjacent integrated device to take over the communication and charging tasks of the current UAV, and triggers the device cooling and maintenance process.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: Through step S1, the drone receives the inspection task instruction from the central management platform and flies along a preset path to collect environmental data in real time, ensuring the automated execution of the detection task, avoiding the problem of low efficiency in traditional manual inspections, and providing continuous input for subsequent data transmission at the same time; through step S2, the drone monitors the remaining battery power and actively generates a charging request signal when the remaining power is lower than the preset power threshold, triggering the device scheduling process of the central management platform, solving the problem of detection interruption caused by insufficient battery life in long tunnel scenarios, and reducing the need for manual battery replacement intervention; through step S3, the central management platform quickly determines the location of the nearest integrated device based on the charging request signal and the tunnel topology map, optimizes resource allocation through a centralized scheduling mechanism, avoids the problem of space occupation caused by the scattered installation of split devices, and shortens the charging waiting time of the drone; through step S4, the drone scans the positioning marker points of the integrated device and calculates the landing deviation, and precisely lands on the telescopic takeoff and landing platform through flight attitude adjustment, eliminating the risk of hardware damage caused by traditional landing errors, and ensuring the precise docking of the wireless charging module and the power receiving coil of the drone; through step S5, the wireless charging module automatically starts charging based on the landing completion signal, and the signal relay module synchronously receives and transmits environmental data. The co-body design of the integrated device avoids electromagnetic interference between the relay module and the charging module, ensuring the synchronous stability of charging efficiency and communication quality; through step S6, the central management platform monitors the charging completion status in real time and generates a new inspection instruction, and the drone continues to execute the remaining tasks according to the instruction, forming a closed-loop process of "detection - charging - task relay", significantly improving the continuous detection efficiency of long tunnels and reducing the repeated inspection cost caused by task interruption.

[0015] Through the synergistic effect of steps S1 to S6, the following beneficial effects are achieved: First, functional integration and dynamic scheduling: The integrated device integrates the signal relay module, the wireless charging module and the telescopic takeoff and landing platform into a single device, reducing the occupation of tunnel space. The central management platform dynamically schedules devices based on the topology map to achieve efficient resource utilization and path optimization; Second, precise control and real-time feedback: The landing deviation calculation in step S4 and the charging start signal in step S5 form a linkage mechanism to ensure charging reliability; The physical isolation design (such as electromagnetic shielding layer) of the signal relay module and the wireless charging module avoids signal interference and ensures the continuity of data transmission; Third, full-process automation: The full chain of automation from charging request triggering, device scheduling, data transmission to task update eliminates the need for manual intervention, reduces operation and maintenance costs, and realizes the long-term autonomous operation of the drone in the tunnel environment. Description of the Drawings

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0017] Figure 1 The figure shows a schematic flowchart of a tunnel safety detection method based on the integration of UAV communication and charging facilities provided by an embodiment of the present invention.

[0018] Figure 2 The figure shows a schematic diagram of the positioning of an integrated device in a tunnel provided by an embodiment of the present invention.

[0019] Figure 3 The figure shows schematic diagrams of the front elevation and side elevation of an integrated device provided by an embodiment of the present invention.

[0020] Figure 4 The figure shows a cross-sectional view of an integrated device embedded in a tunnel provided by an embodiment of the present invention. Specific Embodiments

[0021] To make the purpose, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope protected by the present invention.

[0022] The following will illustrate the specific embodiments of the present invention.

[0023] Combined with Figures 1 to 4 As shown in the figure, the present invention proposes a tunnel safety detection method based on the integration of UAV communication and charging facilities, including: Step S1: The UAV receives the inspection task instruction sent by the central management platform, flies along the tunnel based on a preset path, and collects environmental data in real time; Step S2: The UAV monitors the remaining battery power, and when it is lower than the preset battery power threshold, generates a charging request signal and sends it to the central management platform; Step S3: The central management platform determines the location information of the nearest integrated device based on the charging request signal and the tunnel topology map, and sends it to the UAV. The integrated device includes a signal relay module, a wireless charging module, and a telescopic takeoff and landing platform; Step S4: The UAV scans the positioning marker points of the integrated device according to the location information, calculates the landing deviation, and adjusts the flight attitude before landing on the telescopic takeoff and landing platform; Step S5: The wireless charging module starts charging based on the landing completion signal. Meanwhile, the signal relay module receives environmental data and transmits it back to the central management platform. Step S6: The central management platform monitors the charging completion status, generates a new inspection instruction, and sends it to the drone. The drone then continues to execute the remaining tasks.

[0024] The implementation of this method is based on the collaborative operation of drones, central management platforms, and integrated devices. After receiving the inspection task instructions issued by the central management platform, the drone flies along the preset path and collects environmental data in the tunnel in real time, such as crack, water seepage, or structural deformation information. During the flight, the drone continuously detects the remaining battery power through the on-board battery monitoring module. When the battery power is lower than the preset battery power threshold, a charging request signal is automatically generated and sent to the central management platform. The central management platform combines the stored tunnel topology map to quickly locate the integrated device closest to the drone. This device integrates a signal relay module, a wireless charging module, and a telescopic takeoff and landing platform, and reduces space occupation through embedded design. According to the received integrated device location information, the drone uses lidar to scan the positioning mark points on the surface of the device, calculates the landing deviation through a visual recognition algorithm, and accurately lands on the telescopic takeoff and landing platform after adjusting the pitch angle and roll angle. The wireless charging module immediately starts charging after detecting the landing completion signal. Meanwhile, the signal relay module receives the environmental data collected by the drone and transmits it back to the central management platform through a multi-band antenna. The central management platform monitors the charging progress in real time. After the charging is completed, a new inspection instruction containing the coordinates of the remaining task area is generated, and the drone continues to execute the detection task based on this.

[0025] In the embodiment of the present invention, the communication and charging functions are centrally deployed through the integrated device, avoiding the space occupation and electromagnetic interference of the split device; the dynamic scheduling mechanism shortens the charging waiting time of the drone, improving the detection efficiency of long tunnels; the landing deviation calculation and attitude adjustment ensure the reliability of charging docking, reducing the risk of hardware loss; the full-process automation realizes continuous operation of the drone, reducing the need for manual intervention.

[0026] In some implementation manners, in step S5, Before the wireless charging module starts the charging operation, it scans the surface area of the telescopic takeoff and landing platform through a foreign object detection sensor to obtain surface area image data. The foreign object detection sensor performs feature analysis on the surface area image data. If the contour features of a foreign object are detected, a foreign object alarm signal is generated and sent to the central management platform. Based on the foreign object alarm signal, the central management platform suspends the start instruction of the wireless charging module and sends a maintenance request containing the foreign object position coordinates and surface area image data to the maintenance terminal. After the maintenance terminal receives the maintenance request, it triggers the automatic cleaning of the robotic arm or the manual cleaning process. After removing the foreign object, a cleaning completion signal is generated. After the central management platform receives the cleaning completion signal, it resends the charging start instruction to the wireless charging module to continue the charging operation.

[0027] Before the charging operation is started, the foreign object detection sensor of the integrated device scans the surface of the telescopic take-off and landing platform to obtain high-resolution image data. The sensor is built with an image processing unit that identifies the contour features of foreign objects (such as gravel, tool residues, etc.) through edge detection algorithms. If a foreign object is detected, the system generates an alarm signal containing the coordinates and image of the foreign object and sends it to the central management platform. The platform immediately suspends the charging instruction and sends a maintenance request to the maintenance terminal to trigger the automatic cleaning process. For example, the integrated device can deploy a robotic arm to locate and remove the foreign object according to the foreign object coordinates; or the operator can process it on-site after receiving the alarm information through the maintenance terminal. After the cleaning is completed, the maintenance terminal sends a confirmation signal to the central management platform, and the platform resends the charging instruction, and the wireless charging module resumes operation.

[0028] In an alternative solution, infrared sensors or pressure sensing arrays can be used for foreign object detection to determine the presence of foreign objects through thermal distribution or pressure changes.

[0029] In the embodiments of the present invention, foreign object detection is used to avoid equipment damage or safety hazards caused by foreign objects during the charging process; the automatic cleaning process reduces manual intervention and improves maintenance efficiency; the multi-sensor alternative solution enhances the system adaptability.

[0030] In some implementation manners, in step S3, The central management platform filters multiple candidate integrated devices from the tunnel topology map whose distances from the path nodes are less than a preset distance threshold according to the current flight path of the unmanned aerial vehicle; Based on the real-time communication signal strength value and the charging queue waiting duration of the candidate integrated devices, calculate the comprehensive priority score of each candidate integrated device; Select the target integrated device with the highest comprehensive priority score, extract its position coordinates and communication frequency band information, and encapsulate them as navigation instructions and send them to the unmanned aerial vehicle; After receiving the navigation instructions, the unmanned aerial vehicle updates its flight path based on the position coordinates and switches to the communication frequency band to establish a communication connection with the target integrated device.

[0031] The central management platform filters candidate integrated devices within a certain range of path nodes from the tunnel topology map according to the current flight path of the UAV. During the filtering, the platform combines the real-time position of the UAV with the tunnel structure features (such as bends and forks), and preferentially selects devices with high path coherence. The comprehensive priority score of the candidate devices is obtained by calculating the communication signal strength and the waiting time in the charging queue with weights. For example, the signal strength weight is 60% and the charging queue weight is 40%. After the target device with the highest score is selected, its position coordinates and communication frequency band information are encapsulated as navigation instructions and sent to the UAV. After receiving the instructions, the UAV switches to the communication frequency band of the target device to ensure the stability of signal transmission.

[0032] In an alternative solution, the device health status (such as heat dissipation efficiency) or historical failure rate can be introduced as an additional weight in the priority score.

[0033] The embodiments of the present invention optimize the device utilization rate through a dynamic filtering mechanism, reduce the ineffective flight of the UAV; improve the rationality of scheduling decisions through multi-dimensional scoring; and ensure the continuity of data transmission through communication frequency band switching.

[0034] In some implementation manners, in step S5, After taking over the communication link of the UAV, the signal relay module collects the signal strength values of adjacent integrated devices in real time and generates a signal strength distribution map; If the signal strength value of the current communication link is lower than the preset strength threshold, the adjacent integrated device with the highest signal strength value is selected from the signal strength distribution map as the switching target; Switch the communication link of the UAV to the communication frequency band of the switching target, and continue to transmit environmental data to the central management platform through the switched communication link; The central management platform records the communication link switching event, updates the communication status mark of the corresponding node in the tunnel topology map, and synchronizes the updated map to all integrated devices.

[0035] After taking over the UAV communication link, the signal relay module continuously collects the signal strength data of adjacent integrated devices and generates a real-time signal strength distribution map. The distribution map shows the signal coverage range of each device in the form of a heat map, and the central management platform judges the current link quality based on this. If the signal strength is lower than the threshold (for example, due to tunnel bend occlusion), the system automatically selects the adjacent device with the strongest signal as the switching target. During the switching process, the UAV communication link is briefly switched to the new frequency band, and the environmental data is seamlessly transmitted back through the new link. The central management platform records the switching event and updates the communication node status of the tunnel topology map, such as marking faulty devices or optimizing signal coverage blind spots.

[0036] In an alternative solution, the signal switching can be based on multi-parameter decision-making such as channel occupancy rate or delay index.

[0037] The embodiments of the present invention support intelligent link switching through signal strength distribution maps to avoid communication interruptions; real-time map updates enhance the system's adaptability; and multi-parameter decision-making enhances robustness in complex environments.

[0038] In some implementation manners, in step S4, After receiving the landing request signal from the UAV, the telescopic landing platform drives the platform surface to unfold from the folded state to the horizontal working state through an electric push rod; After the platform surface unfolds, the electromagnetic latch locks the unfolding mechanism and generates a platform ready signal to be sent to the UAV; After receiving the platform ready signal, the UAV scans the positioning marked points on the platform surface through a lidar to obtain the three-dimensional coordinate data of the marked points; Based on the deviation value between the three-dimensional coordinate data and the preset standard coordinates, calculate the flight attitude adjustment parameters, and control the pitch angle and roll angle of the UAV until the plane deviation between the power receiving coil and the transmitting coil is less than the tolerance threshold, and then the landing is completed.

[0039] After the telescopic landing platform receives the landing request from the UAV, the electric push rod drives the platform surface to unfold from the folded state to the horizontal working state. After the unfolding is completed, the electromagnetic latch locks the mechanism to prevent the platform from shaking and sends a ready signal to the UAV. The UAV scans the reflective marked points on the platform surface through a lidar to obtain the three-dimensional coordinate data of the marked points, and calculates the deviation value (such as lateral offset, height error) after comparing with the preset standard coordinates. The flight control system adjusts the thruster thrust according to the deviation value and controls the pitch angle and roll angle of the UAV until the plane deviation between the power receiving coil and the transmitting coil is less than the tolerance threshold (for example, 2 mm).

[0040] In an alternative solution, the positioning marked points can adopt RFID tags or ultrasonic beacons to achieve precise positioning through radio frequency signals or acoustic ranging.

[0041] The embodiments of the present invention ensure the stability of the platform unfolding through electric push rods and electromagnetic latches; achieve millimeter-level landing accuracy through lidar positioning; and multiple positioning technical solutions enhance the system compatibility.

[0042] In some implementation manners, in step S1, During the flight of the UAV, it receives the tunnel obstacle coordinate data real-time pushed by the central management platform through the signal relay module; If the on-board obstacle avoidance sensor of the UAV detects that the obstacle in front conflicts with the current flight path, it generates an obstacle avoidance path planning request and attaches the obstacle size and position information to be sent to the central management platform; The central management platform generates an obstacle avoidance flight path including detour waypoints and speed constraints according to the obstacle information and in combination with the tunnel structure model data; After the UAV receives the obstacle avoidance flight path, it adjusts the thrust distribution of the thrusters, bypasses the obstacle according to the waypoint and speed constraints, and resumes the original preset path to continue the inspection after bypassing.

[0043] During the inspection mission execution, the UAV receives the tunnel obstacle coordinate data pushed by the central management platform in real time through the signal relay module. This data includes the position, size, and type of the obstacle (such as construction equipment, temporary enclosures, or structural debris). The obstacle avoidance sensors carried by the UAV (such as millimeter-wave radar or binocular cameras) continuously scan the forward path. When it detects a conflict between the obstacle and the current flight path, the on-board control system generates an obstacle avoidance path planning request. This request contains the three-dimensional coordinates of the obstacle, volume estimation, and recommended bypass direction, and is sent to the central management platform through the signal relay module. The central management platform combines the tunnel structure model data (such as segment connection methods, clearance dimensions) and real-time obstacle information to generate an obstacle avoidance flight path that includes bypass waypoints, speed limits, and altitude constraints. For example, when encountering a cross-sectional obstacle, the path may include a vertical climb instruction to avoid the top of the obstacle; if the obstacle is located on the side wall, lateral offset waypoints are generated. After the UAV receives the obstacle avoidance path, it performs the bypass action by adjusting the thrust distribution of the thrusters (such as increasing the power of the left rotor to achieve a right offset), and after bypassing the obstacle, it verifies the path clearance through lidar and automatically switches back to the original preset path to continue the inspection.

[0044] In an alternative solution, the obstacle avoidance path planning can adopt a reinforcement learning algorithm to optimize real-time decisions based on historical bypass data.

[0045] The embodiments of the present invention realize the linkage between real-time obstacle information and path planning, significantly improve the obstacle avoidance ability of the UAV; the path generation combined with the tunnel structure model reduces the risk of misjudgment and ensures flight safety; the dynamic thrust adjustment ensures the control accuracy in complex environments; the extensible algorithm framework supports the adaptation of multiple obstacle avoidance strategies.

[0046] In some implementation manners, in step S5, After the wireless charging module aligns the magnetic resonance coupling coil with the power receiving coil of the UAV, it starts to generate charging energy through an alternating magnetic field; During the charging process, the battery temperature and charging voltage data of the UAV are collected in real time through the temperature sensor and voltage sampling circuit; If the battery temperature exceeds the safety threshold or the charging voltage fluctuation exceeds the preset voltage range, the output of the alternating magnetic field is cut off, and a charging fault code including the fault type and timestamp is generated; After receiving the charging fault code, the central management platform schedules the nearest standby integrated device to take over the charging task according to the fault type, or sends a maintenance instruction including the fault type to the maintenance terminal.

[0047] After the wireless charging module starts charging, the magnetic resonance coupling coil and the UAV's power-receiving coil maintain precise alignment, and energy is transmitted through a high-frequency alternating magnetic field. During the charging process, a temperature sensor (such as a thermocouple) continuously monitors the surface temperature of the UAV battery, and a voltage sampling circuit synchronously collects the charging voltage waveform. The monitoring data is transmitted back to the central management platform through a signal relay module. The platform has a built-in safety threshold library (for example, the temperature safety threshold is 55°C, and the voltage fluctuation range is ±5% of the rated value). If it is detected that the battery temperature exceeds the threshold or the voltage is abnormal (such as a sudden increase or decrease), the wireless charging module immediately cuts off the magnetic field output and generates a fault code containing the fault type (overtemperature / overvoltage), timestamp, and device number through a fault encoder. After receiving the fault code, the central management platform executes corresponding measures according to the preset strategy: if it is a temporary fault (such as a momentary voltage fluctuation), it schedules the nearest standby integrated device to take over the charging task; if it is a persistent fault (such as continuous temperature increase caused by battery aging), it sends a maintenance instruction containing the fault details to the maintenance terminal, triggering manual troubleshooting or component replacement. In an alternative solution, current phase analysis technology can be introduced for fault detection, and the abnormal alignment state of the coil can be judged by the magnetic field phase shift.

[0048] The embodiments of the present invention effectively prevent potential safety hazards during the charging process through multi-parameter real-time monitoring; the hierarchical fault handling mechanism improves the system's fault tolerance; and the standby device scheduling reduces the task interruption time.

[0049] In some implementation manners, in step S6, After the UAV finishes charging, the central management platform extracts the coordinate set and priority tags of the remaining uninspected areas; Based on the Euclidean distance between the current position of the UAV and each uninspected area, the area priority weight, and the path complexity factor, the optimal task allocation order is calculated; The optimal task allocation order is encapsulated into a new inspection instruction containing a waypoint sequence and a task time window and sent to the UAV; After the UAV parses the new inspection instruction, it updates the path planning of the on-board navigation system and executes the remaining inspection tasks according to the task time window.

[0050] After the UAV finishes charging, the central management platform extracts the coordinate set and priority tags of the remaining un-inspected areas from the task database (for example, high-risk crack areas are marked as the highest priority). Based on the current position of the UAV, the platform calculates the Euclidean distance between the UAV and each un-inspected area, and combines the regional priority weights (such as the weight coefficient of high-risk areas is 0.7, and that of regular areas is 0.3) and the path complexity factors (such as the number of bends and the length of the vertical climb section). The dynamic programming algorithm is used to generate the optimal task assignment order. For example, areas that are closest and have a high priority are visited first, while avoiding repeated flights caused by path intersections. The optimal order is encapsulated into a new inspection instruction that includes a sequence of waypoints, a task time window (such as a specific area needs to be detected during a specific period), and sensor activation instructions (such as high-precision laser scanning mode). After receiving the instruction, the UAV parses the sequence of waypoints through the on-board navigation system and adjusts its flight speed according to the time window constraint. For example, when approaching the deadline of the task time window, the power of the thruster is automatically increased to ensure timely arrival.

[0051] In an alternative solution, the ant colony algorithm can be used for task assignment to optimize the global task coverage efficiency by simulating the concentration of path pheromones.

[0052] The embodiments of the present invention significantly improve the inspection efficiency through a multi-factor task assignment model; ensure the timely detection of key areas through time window constraints; reduce redundant flight energy consumption through dynamic path parsing; and support complex scenario adaptation through intelligent algorithm expansion.

[0053] In some implementation manners, in step S3, The integrated device collects the temperature, humidity, and harmful gas concentration data in the tunnel in real time through the environmental perception unit, and generates an environmental monitoring data set; The environmental perception unit uploads the environmental monitoring data set to the central management platform through the signal relay module; The central management platform performs statistical analysis on the environmental monitoring data set. If it detects that the temperature exceeds the safety threshold or the harmful gas concentration exceeds the standard, it marks the corresponding coordinates as abnormal areas; Add the coordinates of the abnormal areas to the preset path of the subsequent inspection tasks to collect the environmental data of the abnormal areas.

[0054] The environmental perception unit built in the integrated device collects tunnel environmental data through multiple types of sensors: the temperature sensor monitors the internal heat distribution in the tunnel, the humidity sensor (capacitive type) detects the change in air humidity, and the electrochemical gas sensor detects the concentration of harmful gases (CO, H2S). The collected data set is attached with the device number, timestamp, and location tag, and is uploaded to the central management platform through the signal relay module. The data analysis engine of the platform performs real-time statistical analysis on the data set. For example, it detects sudden temperature changes (such as a rise of more than 5°C within 10 minutes) through the sliding window algorithm, or determines whether the concentration of harmful gases exceeds the standard (such as when the CO concentration exceeds 24 ppm) through threshold comparison. If an anomaly is detected, the platform marks the corresponding coordinates as an abnormal area and assigns high-precision detection instructions (such as infrared thermal imaging scanning or gas concentration gradient measurement) to this area in subsequent inspection tasks. When the drone executes the task, it focuses on detecting the abnormal area according to the updated path, and the collected data is stored separately and a special report is generated. In an alternative solution, the environmental perception unit can integrate a spectral analysis module to improve the gas detection accuracy through laser absorption spectroscopy technology.

[0055] The embodiment of the present invention comprehensively covers tunnel environmental risks through multi-sensor collaborative detection; real-time data analysis improves the efficiency of identifying abnormal areas; high-precision special scanning enhances the ability to detect potential safety hazards; and spectral technology expansion supports the monitoring of more complex pollutants.

[0056] In some implementation manners, in step S5, The integrated device discharges the heat generated during the operation of the wireless charging module and the signal relay module to the outside of the tunnel through a heat dissipation system composed of a heat dissipation fan and a diversion channel; The heat dissipation system monitors the internal temperature of the integrated device in real time through a temperature sensor and dynamically adjusts the rotation speed of the heat dissipation fan according to the temperature value; If the internal temperature continuously exceeds the set temperature threshold, the output power of the wireless charging module is reduced, and an overheat alarm signal containing the device number and temperature value is generated; After receiving the overheat alarm signal, the central management platform schedules adjacent integrated devices to take over the communication and charging tasks of the current drone and triggers the device cooling and maintenance process.

[0057] The heat dissipation system of the integrated device consists of an axial flow cooling fan and a honeycomb-shaped diversion channel. The fan discharges the heat generated during the operation of the wireless charging module and the signal relay module to the outside of the tunnel through the diversion channel. The temperature sensor monitors the temperature data of key parts inside the device (such as the bottom of the charging coil and the signal processing chip) in real time. The central management platform dynamically adjusts the fan speed according to the temperature value (for example, when the temperature rises by 5°C, the speed increases by 20%). If the internal temperature continuously exceeds the set threshold (such as 65°C), the system automatically reduces the output power of the wireless charging module (for example, from 1kW to 500W) and generates an overheat alarm signal including the device number, the peak temperature, and the duration. After receiving the alarm, the central management platform executes a two-level response: if an adjacent integrated device is available, it schedules it to take over the communication and charging tasks of the current drone; if there is no schedulable device, it triggers a forced cooling process (such as starting a thermoelectric cooler) and notifies the maintenance personnel for repair.

[0058] In an alternative solution, the heat dissipation system can adopt heat pipe technology to improve the heat conduction efficiency by using phase change materials.

[0059] The embodiments of the present invention ensure the long-term stable operation of the device through dynamic heat dissipation control; the power adaptive adjustment avoids hardware damage caused by overheating; the multi-level response mechanism minimizes task interruption; and the heat pipe technology enhances the heat dissipation efficiency in high-load scenarios.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A tunnel safety detection method based on the integration of drone communication and charging facilities, characterized in that, Including: Step S1: The drone receives the inspection task instruction sent by the central management platform, flies along the tunnel based on a preset path, and collects environmental data in real time. Step S2: The drone monitors the remaining battery power. When it is lower than the preset battery power threshold, it generates a charging request signal and sends it to the central management platform. Step S3: Based on the charging request signal and the tunnel topology map, the central management platform determines the location information of the nearest integrated device and sends it to the drone. The integrated device includes a signal relay module, a wireless charging module, and a telescopic takeoff and landing platform. Step S4: According to the location information, the drone scans the positioning marker points of the integrated device, calculates the landing deviation, and adjusts its flight attitude to land on the telescopic takeoff and landing platform. Step S5: The wireless charging module starts charging based on the landing completion signal. At the same time, the signal relay module receives the environmental data and transmits it back to the central management platform. Step S6: The central management platform monitors the charging completion status, generates a new inspection instruction, and sends it to the drone. The drone continues to execute the remaining tasks.

2. The method according to claim 1, wherein In step S5, Before the wireless charging module starts the charging operation, it scans the surface area of the telescopic takeoff and landing platform through a foreign object detection sensor to obtain surface area image data. The foreign object detection sensor performs feature analysis on the surface area image data. If a foreign object contour feature is detected, it generates a foreign object warning signal and sends it to the central management platform. Based on the foreign object warning signal, the central management platform suspends the start instruction of the wireless charging module and sends an inspection request including the foreign object position coordinates and surface area image data to the maintenance terminal. After receiving the inspection request, the maintenance terminal triggers an automatic cleaning robotic arm or a manual cleaning process. After clearing the foreign object, it generates a cleaning completion signal. After receiving the cleaning completion signal, the central management platform resends the charging start instruction to the wireless charging module and continues the charging operation.

3. The method according to claim 1, wherein In step S3, The central management platform filters multiple candidate integrated devices with a distance from the path node less than the preset distance threshold from the tunnel topology map according to the current flight path of the drone. Based on the real-time communication signal strength value and the charging queue waiting duration of the candidate integrated devices, calculate the comprehensive priority score of each candidate integrated device. Select the target integrated device with the highest comprehensive priority score, extract its position coordinates and communication frequency band information, and package them as a navigation instruction and send it to the drone. After receiving the navigation instruction, the drone updates its flight path based on the position coordinates and switches to the communication frequency band to establish a communication connection with the target integrated device.

4. The method according to claim 1, wherein In step S5, After taking over the communication link of the drone, the signal relay module collects the signal strength values of adjacent integrated devices in real time and generates a signal strength distribution map. If the signal strength value of the current communication link is lower than the preset strength threshold, select the adjacent integrated device with the highest signal strength value from the signal strength distribution map as the switching target. Switch the communication link of the drone to the communication frequency band of the switching target, and continue to transmit the environmental data to the central management platform through the switched communication link; The central management platform records the communication link switching event, updates the communication status mark of the corresponding node in the tunnel topology map, and synchronizes the updated map to all integrated devices.

5. The method according to claim 1, characterized in that, In step S4, After receiving the landing request signal of the drone, the telescopic take-off and landing platform drives the platform surface to unfold from the folded state to the horizontal working state through the electric push rod; After the platform surface is unfolded, the unfolding mechanism is locked by the electromagnetic bolt, and a platform ready signal is generated and sent to the drone; After receiving the platform ready signal, the drone scans the positioning mark points on the platform surface through the lidar to obtain the three-dimensional coordinate data of the mark points; Based on the deviation value between the three-dimensional coordinate data and the preset standard coordinates, calculate the flight attitude adjustment parameters, and control the pitch angle and roll angle of the drone until the plane deviation between the power receiving coil and the transmitting coil is less than the tolerance threshold, and then complete the landing.

6. The method according to claim 1, wherein In step S1, During the flight of the drone, the tunnel obstacle coordinate data pushed by the central management platform in real time is received through the signal relay module; If the on-board obstacle avoidance sensor of the drone detects that the obstacle in front conflicts with the current flight path, an obstacle avoidance path planning request is generated, and the obstacle size and position information are attached and sent to the central management platform; The central management platform generates an obstacle avoidance flight path including detour waypoints and speed constraints according to the obstacle information and combined with the tunnel structure model data; After receiving the obstacle avoidance flight path, the drone adjusts the thrust distribution of the thrusters, bypasses the obstacle according to the waypoints and speed constraints, and resumes the original preset path to continue the inspection after bypassing.

7. The method according to claim 1, characterized in that In step S5, After the wireless charging module aligns the magnetic resonance coupling coil with the power receiving coil of the drone, an alternating magnetic field is started to generate charging energy; During the charging process, the battery temperature and charging voltage data of the drone are collected in real time through the temperature sensor and the voltage sampling circuit; If the battery temperature exceeds the safety threshold or the charging voltage fluctuation exceeds the preset voltage range, the output of the alternating magnetic field is cut off, and a charging fault code including the fault type and timestamp is generated; After receiving the charging fault code, the central management platform schedules the nearest standby integrated device to take over the charging task according to the fault type, or sends a maintenance instruction including the fault type to the maintenance terminal.

8. The method according to claim 1, wherein In step S6, After the drone is fully charged, the central management platform extracts the coordinate set and priority label of the remaining uninspected areas; Based on the Euclidean distance between the current position of the drone and each uninspected area, the area priority weight and the path complexity factor, calculate the optimal task assignment order; Package the optimal task assignment order into a new inspection instruction including a waypoint sequence and a task time window, and send it to the drone; After parsing the new inspection instruction, the drone updates the path planning of the on-board navigation system and executes the remaining inspection tasks according to the task time window.

9. The method according to claim 1, wherein In step S3, The integrated device collects data on the temperature, humidity, and concentration of harmful gases in the tunnel in real time through the environmental perception unit, and generates an environmental monitoring dataset; The environmental perception unit uploads the environmental monitoring dataset to the central management platform through the signal relay module; The central management platform conducts statistical analysis on the environmental monitoring dataset. If it detects that the temperature exceeds the safety threshold or the concentration of harmful gases exceeds the standard, it marks the corresponding coordinates as an abnormal area; Add the coordinates of the abnormal area to the preset path of the subsequent inspection task to collect environmental data in the abnormal area.

10. The method according to claim 1, wherein In step S5, The integrated device discharges the heat generated during the operation of the wireless charging module and the signal relay module to the outside of the tunnel through a heat dissipation system composed of a heat dissipation fan and a diversion channel; The heat dissipation system monitors the internal temperature of the integrated device in real time through a temperature sensor, and dynamically adjusts the rotation speed of the heat dissipation fan according to the temperature value; If the internal temperature continuously exceeds the set temperature threshold, reduce the output power of the wireless charging module, and generate an overheat warning signal including the device number and the temperature value; After receiving the overheat warning signal, the central management platform schedules adjacent integrated devices to take over the communication and charging tasks of the current drone, and triggers the device cooling and maintenance process.

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