A tunnel safety detection method based on the integration of drone communication and charging facilities

Abstract

The present invention proposes a tunnel safety detection method based on the integration of drone communication and charging facilities, which relates to the technical field of tunnel safety detection. The method integrates the signal relay module, wireless charging module and telescopic take-off and landing platform through integrated equipment, and embeds them into the side wall of the tunnel for deployment, thereby solving the problems of unstable signal, insufficient battery life and large space occupation existing in traditional split equipment. After receiving the inspection task issued by the central management platform, the drone flies along the preset path and collects environmental data in real time; when the battery is insufficient, the platform dynamically dispatches the nearest integrated equipment, and the drone accurately lands on the telescopic take-off and landing platform through laser radar and visual recognition. The wireless charging module starts charging, and the signal relay module transmits data back at the same time. After charging is completed, the platform generates a new task instruction, and the drone continues to perform the remaining inspections.

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 drone communication and charging facilities. Background Art

[0002] Traditional tunnel safety inspections rely on split signal relay stations and independent charging devices, which have the following problems: First, unstable signal coverage: satellite signals are blocked in the tunnel, and the drone communication link is easily interrupted, resulting in failure to transmit detection data back; Second, insufficient endurance: In long-distance tunnel environments, it is difficult for drones to cover the entire distance in a single flight, and frequent returns or manual battery replacement are required, resulting in low detection efficiency; Third, space occupation and electromagnetic interference: Split equipment is installed in a dispersed manner, occupying tunnel space, and when the relay module and the charging device coexist in close proximity, electromagnetic interference causes communication quality to deteriorate or charging efficiency to decrease; Fourth, high maintenance costs: The independent deployment of multiple devices requires frequent maintenance, and manual intervention affects the normal operation of the tunnel.

[0003] Although there are existing technologies that attempt to apply drones to tunnel inspections, it is still difficult to achieve efficient, continuous and autonomous safety inspections due to the above-mentioned problems. Summary of the Invention

[0004] In response to the above-mentioned problems existing in the prior art, the present invention proposes a tunnel safety detection method based on the integration of drone communication and charging facilities, comprising:

[0005] Step S1: The drone 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;

[0006] Step S2: The drone monitors the remaining power and, when the remaining power falls below a preset power threshold, generates a charging request signal and sends it to the central management platform;

[0007] Step S3: Based on the charging request signal and the tunnel topology map, the central management platform determines the location 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 retractable take-off and landing platform.

[0008] Step S4: The UAV scans the positioning mark points of the integrated equipment based on the location information and calculates the landing deviation, adjusts the flight attitude, and then lands on the telescopic take-off and landing platform;

[0009] Step S5: The wireless charging module starts charging based on the landing completion signal, while the signal relay module receives environmental data and transmits it back to the central management platform;

[0010] Step S6: The central management platform monitors the charging completion status, generates a new inspection instruction and sends it to the drone, which then continues to perform the remaining tasks.

[0011] In some implementations, in step S5,

[0012] Before the wireless charging module starts the charging operation, the foreign object detection sensor scans the surface area of ​​the telescopic take-off and landing platform to obtain image data of the surface area;

[0013] The foreign object detection sensor performs feature analysis on the surface area image data. If the foreign object contour features are detected, a foreign object alarm signal is generated and sent to the central management platform.

[0014] Based on the foreign object alarm signal, the central management platform suspends the start-up instruction of the wireless charging module and sends a maintenance request containing the foreign object location coordinates and surface area image data to the maintenance terminal;

[0015] After receiving the maintenance request, the maintenance terminal triggers the automatic cleaning robot arm or the manual cleaning process, and generates a cleaning completion signal after removing foreign objects;

[0016] After receiving the cleaning completion signal, the central management platform resends the charging start instruction to the wireless charging module to continue the charging operation.

[0017] In some implementations, in step S3,

[0018] Based on the current flight path of the UAV, the central management platform selects multiple candidate integrated devices from the tunnel topology map whose distance from the path node is less than a preset distance threshold;

[0019] Calculate the comprehensive priority score of each candidate integrated device based on the real-time communication signal strength value and charging queue waiting time of the candidate integrated device;

[0020] Select the target integrated device with the highest comprehensive priority score, extract its location coordinates and communication frequency band information, encapsulate it into navigation instructions and send it to the drone;

[0021] After receiving the navigation instructions, the UAV updates the flight path based on the location coordinates and switches to the communication frequency band to establish a communication connection with the target integrated device.

[0022] In some implementations, in step S5,

[0023] After taking over the UAV's communication link, the signal relay module collects the signal strength values ​​of adjacent integrated devices in real time and generates a signal strength distribution map;

[0024] 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;

[0025] Switch the UAV's communication link to the target communication frequency band, and continue to transmit environmental data to the central management platform through the switched communication link;

[0026] The central management platform records communication link switching events, updates the communication status marks of corresponding nodes in the tunnel topology map, and synchronizes the updated map to all integrated devices.

[0027] In some implementations, in step S4,

[0028] After receiving the landing request signal from the UAV, the telescopic take-off and landing platform drives the platform surface from the folded state to the horizontal working state through the electric push rod;

[0029] After the platform surface is deployed, the deployment mechanism is locked by an electromagnetic latch and a platform ready signal is generated and sent to the UAV;

[0030] After receiving the platform ready signal, the UAV scans the positioning mark points on the platform surface through the lidar to obtain the three-dimensional coordinate data of the mark points;

[0031] Based on the deviation between the three-dimensional coordinate data and the preset standard coordinates, the flight attitude adjustment parameters are calculated to control the pitch angle and roll angle of the drone until the plane deviation between the receiving coil and the transmitting coil is less than the tolerance threshold and the landing is completed.

[0032] In some implementations, in step S1,

[0033] During the flight, the drone receives tunnel obstacle coordinate data pushed in real time by the central management platform through the signal relay module;

[0034] If the drone's onboard obstacle avoidance sensor detects that an obstacle ahead conflicts with the current flight path, it generates an obstacle avoidance path planning request and sends it to the central management platform with the obstacle's size and location information attached.

[0035] The central management platform generates an obstacle avoidance flight path that includes detour waypoints and speed constraints based on obstacle information and tunnel structure model data.

[0036] After receiving the obstacle avoidance flight path, the drone adjusts the thrust distribution of the propellers, bypasses the obstacle according to the waypoint and speed constraints, and resumes the original preset path to continue inspection after bypassing the obstacle.

[0037] In some implementations, in step S5,

[0038] The wireless charging module aligns the magnetic resonance coupling coil with the drone's power receiving coil and activates the alternating magnetic field to generate charging energy.

[0039] During the charging process, the temperature sensor and voltage sampling circuit collect the drone's battery temperature and charging voltage data in real time;

[0040] If the battery temperature exceeds the safety threshold or the charging voltage fluctuation exceeds the preset voltage range, the alternating magnetic field output is cut off and a charging fault code containing the fault type and timestamp is generated;

[0041] After receiving the charging fault code, the central management platform dispatches the nearest backup integrated equipment to take over the charging task according to the fault type, or sends a maintenance instruction containing the fault type to the maintenance terminal.

[0042] In some implementations, in step S6,

[0043] After the drone is fully charged, the central management platform extracts the coordinates and priority tags of the remaining uninspected areas;

[0044] Calculate the optimal task allocation sequence based on the Euclidean distance between the drone's current location and each uninspected area, the area priority weight, and the path complexity factor;

[0045] The optimal task allocation sequence is encapsulated into a new inspection instruction containing a waypoint sequence and a task time window, and sent to the UAV;

[0046] After parsing the new inspection instructions, the drone updates the path planning of the onboard navigation system and executes the remaining inspection tasks according to the mission time window.

[0047] In some implementations, in step S3,

[0048] The integrated equipment collects real-time data on temperature, humidity, and harmful gas concentrations in the tunnel through the environmental sensing unit to generate an environmental monitoring data set;

[0049] The environmental perception unit uploads the environmental monitoring data set to the central management platform through the signal relay module;

[0050] The central management platform performs statistical analysis on environmental monitoring data sets. If it detects that the temperature exceeds the safety threshold or the concentration of harmful gases exceeds the standard, the corresponding coordinates are marked as abnormal areas;

[0051] Add the coordinates of the abnormal area to the preset path of subsequent inspection tasks to collect environmental data of the abnormal area.

[0052] In some implementations, in step S5,

[0053] The integrated equipment uses a cooling system consisting of a cooling fan and a guide channel to discharge the heat generated by the wireless charging module and signal relay module to the outside of the tunnel;

[0054] The cooling system monitors the internal temperature of the integrated equipment in real time through temperature sensors and dynamically adjusts the speed of the cooling fan according to the temperature value;

[0055] If the internal temperature continues to exceed the set temperature threshold, the output power of the wireless charging module is reduced and an overheating alarm signal containing the device number and temperature value is generated;

[0056] After receiving the overheating alarm signal, the central management platform dispatches adjacent integrated equipment to take over the communication and charging tasks of the current drone and triggers the equipment cooling maintenance process.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] Through step S1, the UAV receives the inspection task instruction of the central management platform and flies along the preset path, collecting environmental data in real time to ensure the automatic execution of the inspection task, avoiding the problem of low efficiency of traditional manual inspection, and providing continuous input for subsequent data transmission; through step S2, the UAV monitors the remaining power and actively generates a charging request signal when it is lower than the preset power threshold, triggering the equipment scheduling process of the central management platform, solving the problem of inspection interruption caused by insufficient battery life in long tunnel scenarios, and reducing the need for manual intervention to replace batteries; through step S3, the central management platform quickly determines the location of the nearest integrated equipment based on the charging request signal and the tunnel topology map, optimizes resource allocation through a centralized scheduling mechanism, avoids the space occupation problem caused by the scattered installation of split equipment, and shortens the waiting time for UAV charging; through step S 4. The drone scans the positioning mark points of the integrated equipment and calculates the landing deviation. It accurately lands on the retractable take-off and landing platform by adjusting its flight attitude, eliminating the risk of hardware damage caused by traditional landing errors and ensuring the precise docking of the wireless charging module and the drone's power receiving coil. In step S5, the wireless charging module automatically starts charging based on the landing completion signal, and the signal relay module simultaneously receives and transmits environmental data. The co-integrated design of the integrated equipment avoids electromagnetic interference between the relay module and the charging module, ensuring the simultaneous stability of charging efficiency and communication quality. In step S6, the central management platform monitors the charging completion status in real time and generates new inspection instructions. The drone continues to perform the remaining tasks according to the instructions, forming a closed-loop process of "inspection-charging-task relay", significantly improving the continuous inspection efficiency of long tunnels and reducing the cost of repeated inspections caused by task interruptions.

[0059] Through the synergistic effect of steps S1 to S6, the following beneficial effects are achieved: First, functional integration and dynamic scheduling: the integrated equipment integrates the signal relay module, wireless charging module and telescopic take-off and landing platform into a single device, reducing the space occupied by the tunnel. The central management platform dynamically schedules equipment based on the topological 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 of the signal relay module and the wireless charging module (such as the electromagnetic shielding layer) avoids signal interference and ensures the continuity of data return; Third, full process automation: the full chain automation from charging request triggering, equipment scheduling, data return to task update eliminates the need for manual intervention, reduces operation and maintenance costs, and realizes long-term autonomous operation of drones in tunnel environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0061] Figure 1 The figure shows a flow chart of a tunnel safety detection method based on the integration of drone communication and charging facilities provided by one embodiment of the present invention.

[0062] Figure 2 FIG2 is a schematic diagram showing the positioning of an integrated device provided by an embodiment of the present invention in a tunnel.

[0063] Figure 3 Shown are schematic diagrams of the front elevation and side elevation of an integrated device provided by one embodiment of the present invention.

[0064] Figure 4 Shown is a cross-sectional view of an integrated device provided by an embodiment of the present invention embedded in a tunnel. DETAILED DESCRIPTION

[0065] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0066] The specific embodiments of the present invention are described below.

[0067] Combine Figures 1 to 4 As shown, the present invention proposes a tunnel safety detection method based on the integration of drone communication and charging facilities, comprising:

[0068] Step S1: The drone 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;

[0069] Step S2: The drone monitors the remaining power and, when the remaining power falls below a preset power threshold, generates a charging request signal and sends it to the central management platform;

[0070] Step S3: Based on the charging request signal and the tunnel topology map, the central management platform determines the location 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 retractable take-off and landing platform.

[0071] Step S4: The UAV scans the positioning mark points of the integrated equipment based on the location information and calculates the landing deviation, adjusts the flight attitude, and then lands on the telescopic take-off and landing platform;

[0072] Step S5: The wireless charging module starts charging based on the landing completion signal, while the signal relay module receives environmental data and transmits it back to the central management platform;

[0073] Step S6: The central management platform monitors the charging completion status, generates a new inspection instruction and sends it to the drone, which then continues to perform the remaining tasks.

[0074] This method relies on the collaborative operation of drones, a central management platform, and integrated equipment. After receiving inspection mission instructions from the central management platform, the drone flies along a pre-set route and collects real-time environmental data within the tunnel, such as cracks, water seepage, and structural deformation. During flight, the drone continuously monitors its remaining battery life using an onboard power monitoring module. When the battery level falls below a preset threshold, it automatically generates a charging request signal and sends it to the central management platform. The central management platform, using a stored tunnel topology map, quickly locates the integrated equipment closest to the drone. This equipment integrates a signal relay module, a wireless charging module, and a retractable take-off and landing platform, utilizing an embedded design to minimize space usage. Based on the received integrated equipment location information, the drone uses a lidar scanner to scan the positioning markers on the device's surface. Using a visual recognition algorithm, the drone calculates landing deviation, adjusts its pitch and roll angles, and precisely lands on the retractable take-off and landing platform. Upon detecting the landing completion signal, the wireless charging module immediately initiates charging. Simultaneously, the signal relay module receives environmental data collected by the drone and transmits it back to the central management platform via a multi-band antenna. The central management platform monitors the charging progress in real time. After charging is completed, it generates a new inspection instruction containing the coordinates of the remaining task area, and the drone continues to perform the inspection task accordingly.

[0075] The embodiments of the present invention centrally deploy communication and charging functions through integrated equipment, avoiding the space occupation and electromagnetic interference of separate equipment; shortening the charging waiting time of drones through a dynamic scheduling mechanism, improving the efficiency of long tunnel inspection; ensuring the reliability of charging docking and reducing the risk of hardware loss through landing deviation calculation and posture adjustment; and realizing continuous operation of drones through full process automation, reducing the need for human intervention.

[0076] In some implementations, in step S5,

[0077] Before the wireless charging module starts the charging operation, the foreign object detection sensor scans the surface area of ​​the telescopic take-off and landing platform to obtain image data of the surface area;

[0078] The foreign object detection sensor performs feature analysis on the surface area image data. If the foreign object contour features are detected, a foreign object alarm signal is generated and sent to the central management platform.

[0079] Based on the foreign object alarm signal, the central management platform suspends the start-up instruction of the wireless charging module and sends a maintenance request containing the foreign object location coordinates and surface area image data to the maintenance terminal;

[0080] After receiving the maintenance request, the maintenance terminal triggers the automatic cleaning robot arm or the manual cleaning process, and generates a cleaning completion signal after removing foreign objects;

[0081] After receiving the cleaning completion signal, the central management platform resends the charging start instruction to the wireless charging module to continue the charging operation.

[0082] Before charging begins, the integrated device's foreign object detection sensor scans the surface of the telescopic lift platform, acquiring high-resolution image data. The sensor's built-in image processing unit uses an edge detection algorithm to identify the contour features of foreign objects (such as gravel and tool residue). If a foreign object is detected, the system generates an alarm signal containing the object's coordinates and image and sends it to the central management platform. The platform immediately suspends charging instructions and sends a maintenance request to the maintenance terminal, triggering an automated cleaning process. For example, the integrated device can deploy a robotic arm to locate and remove the foreign object based on its coordinates; alternatively, a human operator can receive an alarm message through the maintenance terminal and handle the problem on-site. Once cleaning is complete, the maintenance terminal sends a confirmation signal to the central management platform, which then reissues the charging command, resuming operation of the wireless charging module.

[0083] As an alternative, foreign object detection can use infrared sensors or pressure sensing arrays to determine the presence of foreign objects through heat distribution or pressure changes.

[0084] The embodiments of the present invention avoid device damage or safety hazards caused by foreign objects during charging through foreign object detection; reduce manual intervention and improve maintenance efficiency through automated cleaning processes; and enhance system adaptability through multi-sensor alternative solutions.

[0085] In some implementations, in step S3,

[0086] Based on the current flight path of the UAV, the central management platform selects multiple candidate integrated devices from the tunnel topology map whose distance from the path node is less than a preset distance threshold;

[0087] Calculate the comprehensive priority score of each candidate integrated device based on the real-time communication signal strength value and charging queue waiting time of the candidate integrated device;

[0088] Select the target integrated device with the highest comprehensive priority score, extract its location coordinates and communication frequency band information, encapsulate it into navigation instructions and send it to the drone;

[0089] After receiving the navigation instructions, the UAV updates the flight path based on the location coordinates and switches to the communication frequency band to establish a communication connection with the target integrated device.

[0090] Based on the drone's current flight path, the central management platform screens candidate integrated devices from the tunnel topology map within a certain range of path nodes. During this screening process, the platform considers the drone's real-time location and tunnel structural features (such as curves and forks), prioritizing devices with high path continuity. A comprehensive priority score for the candidate devices is calculated by weighting communication signal strength and charging queue wait time, for example, with a signal strength weight of 60% and a charging queue weight of 40%. The highest-scoring target device is selected, and its location coordinates and communication frequency band information are encapsulated as navigation commands and sent to the drone. Upon receiving the commands, the drone switches to the target device's communication frequency band to ensure stable signal transmission.

[0091] Alternatively, the priority score can incorporate device health (e.g., cooling efficiency) or historical failure rates as additional weights.

[0092] The embodiments of the present invention optimize equipment utilization through a dynamic screening mechanism to reduce ineffective drone flights; improve the rationality of scheduling decisions through multi-dimensional scoring; and ensure data transmission continuity through communication frequency band switching.

[0093] In some implementations, in step S5,

[0094] After taking over the UAV's communication link, the signal relay module collects the signal strength values ​​of adjacent integrated devices in real time and generates a signal strength distribution map;

[0095] 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;

[0096] Switch the UAV's communication link to the target communication frequency band, and continue to transmit environmental data to the central management platform through the switched communication link;

[0097] The central management platform records communication link switching events, updates the communication status marks of corresponding nodes in the tunnel topology map, and synchronizes the updated map to all integrated devices.

[0098] After taking over the drone's communication link, the signal relay module continuously collects signal strength data from adjacent integrated devices and generates a real-time signal strength distribution map. This distribution map displays the signal coverage of each device in the form of a heat map, which the central management platform uses to determine the current link quality. If the signal strength falls below a threshold (for example, due to obstruction caused by a tunnel curve), the system automatically selects the adjacent device with the strongest signal as the switching target. During the switching process, the drone's communication link briefly switches to the new frequency band, and environmental data is seamlessly transmitted back over the new link. The central management platform records the switching event and updates the communication node status on the tunnel topology map, for example, to mark faulty devices or optimize signal coverage blind spots.

[0099] In an alternative solution, signal switching can be based on multi-parameter decisions such as channel occupancy or delay indicators.

[0100] The embodiments of the present invention support intelligent link switching through a signal strength distribution map to avoid communication interruption; real-time map updates improve system adaptability; and multi-parameter decision-making enhances robustness in complex environments.

[0101] In some implementations, in step S4,

[0102] After receiving the landing request signal from the UAV, the telescopic take-off and landing platform drives the platform surface from the folded state to the horizontal working state through the electric push rod;

[0103] After the platform surface is deployed, the deployment mechanism is locked by an electromagnetic latch and a platform ready signal is generated and sent to the UAV;

[0104] After receiving the platform ready signal, the UAV scans the positioning mark points on the platform surface through the lidar to obtain the three-dimensional coordinate data of the mark points;

[0105] Based on the deviation between the three-dimensional coordinate data and the preset standard coordinates, the flight attitude adjustment parameters are calculated to control the pitch angle and roll angle of the drone until the plane deviation between the receiving coil and the transmitting coil is less than the tolerance threshold and the landing is completed.

[0106] After the telescopic take-off and landing platform receives a landing request from the drone, an electric actuator drives the platform surface from a folded state to a horizontal operating position. Once deployed, an electromagnetic latch locks the mechanism to prevent the platform from shaking and sends a ready signal to the drone. The drone uses a lidar to scan reflective markers on the platform surface, acquiring the three-dimensional coordinate data of these markers. This data is then compared with the preset standard coordinates and the deviations (e.g., lateral offset, altitude error) are calculated. The flight control system adjusts the thrust of the thrusters based on these deviations, controlling the drone's pitch and roll angles until the plane deviation between the receiving and transmitting coils falls within a tolerance threshold (e.g., 2mm).

[0107] As an alternative, RFID tags or ultrasonic beacons can be used to locate markers, achieving precise positioning through radio frequency signals or sound wave ranging.

[0108] The embodiment of the present invention ensures the stability of platform deployment through electric push rods and electromagnetic latches; achieves millimeter-level landing accuracy through laser radar positioning; and enhances system compatibility through multiple positioning technology solutions.

[0109] In some implementations, in step S1,

[0110] During the flight, the drone receives tunnel obstacle coordinate data pushed in real time by the central management platform through the signal relay module;

[0111] If the drone's onboard obstacle avoidance sensor detects that an obstacle ahead conflicts with the current flight path, it generates an obstacle avoidance path planning request and sends it to the central management platform with the obstacle's size and location information attached.

[0112] The central management platform generates an obstacle avoidance flight path that includes detour waypoints and speed constraints based on obstacle information and tunnel structure model data.

[0113] After receiving the obstacle avoidance flight path, the drone adjusts the thrust distribution of the propellers, bypasses the obstacle according to the waypoint and speed constraints, and resumes the original preset path to continue inspection after bypassing the obstacle.

[0114] During inspections, drones receive real-time tunnel obstacle coordinate data from the central management platform via a signal relay module. This data includes the location, size, and type of obstacles (such as construction equipment, temporary fencing, or structural debris). The drone's onboard obstacle avoidance sensors (such as millimeter-wave radar or binocular cameras) continuously scan the path ahead. When an obstacle is detected that conflicts with the current flight path, the onboard control system generates an obstacle avoidance path planning request. This request, which includes the obstacle's 3D coordinates, volume estimate, and suggested detour direction, is sent to the central management platform via the signal relay module. The central management platform combines tunnel structural model data (such as segment connection structure and clearance dimensions) with real-time obstacle information to generate an obstacle avoidance flight path with detour waypoints, speed limits, and altitude constraints. For example, when encountering a cross-sectional obstacle, the path might include a vertical climb command to avoid the top of the obstacle; if the obstacle is located on the sidewall, a lateral offset waypoint is generated. After receiving the obstacle avoidance path, the drone performs a circumvention action by adjusting the thrust distribution of the propeller (such as increasing the power of the left rotor to achieve right deviation). After bypassing the obstacle, it verifies the path's smoothness through the lidar and automatically switches back to the original preset path to continue inspection.

[0115] As an alternative, obstacle avoidance path planning can use reinforcement learning algorithms to optimize real-time decisions based on historical detour data.

[0116] The embodiments of the present invention realize the linkage between real-time obstacle information and path planning, significantly improving the obstacle avoidance capability of the UAV; combining the path generation of the tunnel structure model to reduce the risk of misjudgment and ensure flight safety; dynamic thrust adjustment ensures control accuracy in complex environments; and the scalable algorithm framework supports the adaptation of multiple obstacle avoidance strategies.

[0117] In some implementations, in step S5,

[0118] The wireless charging module aligns the magnetic resonance coupling coil with the drone's power receiving coil and activates the alternating magnetic field to generate charging energy.

[0119] During the charging process, the temperature sensor and voltage sampling circuit collect the drone's battery temperature and charging voltage data in real time;

[0120] If the battery temperature exceeds the safety threshold or the charging voltage fluctuation exceeds the preset voltage range, the alternating magnetic field output is cut off and a charging fault code containing the fault type and timestamp is generated;

[0121] After receiving the charging fault code, the central management platform dispatches the nearest backup integrated equipment to take over the charging task according to the fault type, or sends a maintenance instruction containing the fault type to the maintenance terminal.

[0122] After the wireless charging module initiates charging, the magnetic resonance coupling coil maintains precise alignment with the drone's power receiving coil, transmitting energy through a high-frequency alternating magnetic field. During charging, a temperature sensor (such as a thermocouple) monitors the drone's battery surface temperature in real time, and a voltage sampling circuit simultaneously collects the charging voltage waveform. This monitoring data is transmitted back to the central management platform via a signal relay module. The platform has a built-in safety threshold library (e.g., a temperature safety threshold of 55°C and a voltage fluctuation range of ±5% of the rated value). If 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 using the fault encoder, including the fault type (overtemperature / overvoltage), timestamp, and device number. Upon receiving the fault code, the central management platform implements a pre-defined response strategy. If the fault is temporary (such as a momentary voltage fluctuation), the nearest backup integrated device is dispatched to take over the charging task. If the fault is persistent (such as a persistent temperature increase due to battery aging), a repair instruction containing fault details is sent to the maintenance terminal, triggering manual troubleshooting or component replacement. Alternatively, fault detection can incorporate current phase analysis technology to determine whether the coil alignment is abnormal based on magnetic field phase shift.

[0123] The embodiments of the present invention effectively prevent potential safety hazards during the charging process through real-time monitoring of multiple parameters; a hierarchical fault handling mechanism improves the system's fault tolerance; and backup equipment scheduling reduces task interruption time.

[0124] In some implementations, in step S6,

[0125] After the drone is fully charged, the central management platform extracts the coordinates and priority tags of the remaining uninspected areas;

[0126] Calculate the optimal task allocation sequence based on the Euclidean distance between the drone's current location and each uninspected area, the area priority weight, and the path complexity factor;

[0127] The optimal task allocation sequence is encapsulated into a new inspection instruction containing a waypoint sequence and a task time window, and sent to the UAV;

[0128] After parsing the new inspection instructions, the drone updates the path planning of the onboard navigation system and executes the remaining inspection tasks according to the mission time window.

[0129] After the drones have finished charging, the central management platform extracts the coordinates and priority tags of the remaining uninspected areas from the mission database (e.g., high-risk crack areas are marked as the highest priority). Based on the drone's current location, the platform calculates the Euclidean distance to each uninspected area. This, combined with regional priority weights (e.g., a weight coefficient of 0.7 for high-risk areas and 0.3 for standard areas) and path complexity factors (e.g., the number of curves and the length of vertical climbs), uses a dynamic programming algorithm to generate the optimal mission allocation sequence. For example, it prioritizes the closest, high-priority areas while avoiding duplicate flights caused by intersecting paths. This optimal sequence is encapsulated as a new inspection command containing a waypoint sequence, a mission time window (e.g., an area must be inspected within a specific time period), and sensor activation instructions (e.g., high-precision laser scanning mode). Upon receiving the command, the drone uses its onboard navigation system to interpret the waypoint sequence and adjust its flight speed based on the time window constraints. For example, it automatically increases thruster power near the end of the mission time window to ensure on-time arrival.

[0130] In the alternative, task allocation can adopt the ant colony algorithm to optimize the global task coverage efficiency by simulating the path pheromone concentration.

[0131] The embodiments of the present invention significantly improve inspection efficiency through a multi-factor task allocation model; ensure timely detection of key areas through time window constraints; reduce redundant flight energy consumption through dynamic path resolution; and support adaptation to complex scenarios through intelligent algorithm expansion.

[0132] In some implementations, in step S3,

[0133] The integrated equipment collects real-time data on temperature, humidity, and harmful gas concentrations in the tunnel through the environmental sensing unit to generate an environmental monitoring data set;

[0134] The environmental perception unit uploads the environmental monitoring data set to the central management platform through the signal relay module;

[0135] The central management platform performs statistical analysis on environmental monitoring data sets. If it detects that the temperature exceeds the safety threshold or the concentration of harmful gases exceeds the standard, the corresponding coordinates are marked as abnormal areas;

[0136] Add the coordinates of the abnormal area to the preset path of subsequent inspection tasks to collect environmental data of the abnormal area.

[0137] The integrated equipment's built-in environmental perception unit collects tunnel environmental data using multiple sensor types: a temperature sensor monitors heat distribution within the tunnel, a capacitive humidity sensor detects changes in air humidity, and an electrochemical gas sensor measures the concentration of hazardous gases (CO and H2S). The collected data sets are tagged with a device ID, timestamp, and location, and uploaded to the central management platform via a signal relay module. The platform's data analysis engine performs real-time statistical analysis on the data sets, using, for example, a sliding window algorithm to detect sudden temperature changes (e.g., a temperature rise exceeding 5°C within 10 minutes) or threshold comparison to determine if hazardous gas concentrations exceed the specified limit (e.g., CO concentration exceeding 24 ppm). If an anomaly is detected, the platform marks the corresponding coordinates as an abnormal area and assigns high-precision inspection instructions (such as infrared thermal imaging scans or gas concentration gradient measurements) to that area during subsequent inspections. During the drone's mission, it focuses on the abnormal area based on the updated route, stores the collected data separately, and generates a dedicated report. Alternatively, the environmental perception unit can integrate a spectral analysis module, using laser absorption spectroscopy to improve gas detection accuracy.

[0138] The embodiments of the present invention comprehensively cover 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 safety hazards; and spectral technology expansion supports more complex pollutant monitoring.

[0139] In some implementations, in step S5,

[0140] The integrated equipment uses a cooling system consisting of a cooling fan and a guide channel to discharge the heat generated by the wireless charging module and signal relay module to the outside of the tunnel;

[0141] The cooling system monitors the internal temperature of the integrated equipment in real time through temperature sensors and dynamically adjusts the speed of the cooling fan according to the temperature value;

[0142] If the internal temperature continues to exceed the set temperature threshold, the output power of the wireless charging module is reduced and an overheating alarm signal containing the device number and temperature value is generated;

[0143] After receiving the overheating alarm signal, the central management platform dispatches adjacent integrated equipment to take over the communication and charging tasks of the current drone and triggers the equipment cooling maintenance process.

[0144] The integrated device's cooling system consists of an axial-flow fan and honeycomb-shaped diversion channels. The fan dissipates heat generated by the wireless charging module and signal relay module through the diversion channels to the outside of the tunnel. Temperature sensors monitor real-time temperature data at key internal components of the device (such as the base of the charging coil and the signal processing chip). The central management platform dynamically adjusts fan speed based on temperature (e.g., a 20% increase for every 5°C increase in temperature). If the internal temperature persistently exceeds a set threshold (e.g., 65°C), the system automatically reduces the output power of the wireless charging module (e.g., from 1kW to 500W) and generates an overheating alarm signal containing the device number, peak temperature, and duration. Upon receiving the alarm, the central management platform implements a two-tiered response: if a neighboring integrated device is available, it dispatches it to take over communication and charging tasks for the current drone; if no dispatchable device is available, a forced cooling process (e.g., activating a semiconductor cooler) is triggered and maintenance personnel are notified for repair.

[0145] As an alternative, the cooling system can adopt heat pipe technology and use phase change materials to improve heat conduction efficiency.

[0146] The embodiments of the present invention ensure long-term stable operation of the equipment through dynamic heat dissipation control; adaptive power adjustment avoids hardware damage caused by overheating; a multi-level response mechanism minimizes task interruptions; and heat pipe technology enhances heat dissipation efficiency in high-load scenarios.

[0147] 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 it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions 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: include: Step S1: The drone 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 drone monitors the remaining power, and when the remaining power is lower than a preset 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 drone. 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 mark points of the integrated equipment according to the position information and calculates the landing deviation, adjusts the flight attitude and then lands on the telescopic take-off and landing platform; Step S5: the wireless charging module starts charging based on the landing completion signal, and 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, and the drone continues to perform the remaining tasks; Wherein, in the step S5, before the wireless charging module starts the charging operation, the foreign object detection sensor scans the surface area of ​​the telescopic take-off and landing platform to obtain surface area image data; The foreign object detection sensor performs feature analysis on the surface area image data, and if a foreign object contour feature is detected, generates a foreign object alarm signal and sends it to the central management platform; The central management platform suspends the activation instruction of the wireless charging module based on the foreign object alarm signal, and sends a maintenance request including the foreign object position coordinates and surface area image data to the maintenance terminal; After receiving the maintenance request, the maintenance terminal triggers an automatic cleaning robot arm or a manual cleaning process, and generates a cleaning completion signal after removing foreign matter; After receiving the cleaning completion signal, the central management platform resends the charging start instruction to the wireless charging module to continue the charging operation.

2. The method according to claim 1, characterized in that In the step S3, The central management platform selects, from the tunnel topology map, a plurality of candidate integrated devices whose distances to path nodes are less than a preset distance threshold based on the current flight path of the UAV; Calculating a comprehensive priority score for each candidate integrated device based on the real-time communication signal strength value and charging queue waiting time of the candidate integrated device; Select the target integrated device with the highest comprehensive priority score, extract its location coordinates and communication frequency band information, encapsulate it into a navigation command and send it to the UAV; After receiving the navigation instruction, the UAV 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.

3. The method according to claim 1, characterized in that In the 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 a preset strength threshold, selecting the adjacent integrated device with the highest signal strength value from the signal strength distribution map as the switching target; Switching the communication link of the UAV to the communication frequency band of the switching target, and continuing 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.

4. The method according to claim 1, wherein In the step S4, After receiving the landing request signal from the UAV, the telescopic take-off and landing platform drives the platform surface to unfold from a folded state to a horizontal working state through an electric push rod; After the platform surface is deployed, the deployment mechanism is locked by an electromagnetic latch, and a platform ready signal is generated and sent to the UAV; After receiving the platform ready signal, the UAV scans the positioning mark points on the surface of the platform through the laser radar 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, the flight attitude adjustment parameters are calculated to control the pitch angle and roll angle of the UAV until the plane deviation between the receiving coil and the transmitting coil is less than the tolerance threshold and the landing is completed.

5. The method according to claim 1, wherein In the step S1, During the flight, the UAV receives the tunnel obstacle coordinate data pushed in real time by the central management platform through the signal relay module; If the obstacle avoidance sensor onboard the drone detects that the obstacle ahead conflicts with the current flight path, it generates an obstacle avoidance path planning request and attaches the obstacle size and location information to send it to the central management platform; The central management platform generates an obstacle avoidance flight path including detour waypoints and speed constraints based on obstacle information and combined with tunnel structure model data; After receiving the obstacle avoidance flight path, the UAV adjusts the thrust distribution of the propeller, bypasses the obstacle according to the waypoint and speed constraints, and resumes the original preset path to continue inspection after bypassing the obstacle.

6. The method according to claim 1, characterized in that In the step S5, The wireless charging module aligns the magnetic resonance coupling coil with the power receiving coil of the drone and activates the alternating magnetic field 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 a safety threshold or the charging voltage fluctuation exceeds a preset voltage range, the alternating magnetic field output is cut off and a charging fault code including a fault type and a timestamp is generated; After receiving the charging fault code, the central management platform dispatches the nearest standby integrated equipment to take over the charging task according to the fault type, or sends a maintenance instruction containing the fault type to the maintenance terminal.

7. The method according to claim 1, characterized in that In the step S6, After the UAV is fully charged, the central management platform extracts the coordinate sets and priority tags of the remaining uninspected areas; Calculate the optimal task allocation sequence 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; Encapsulating the optimal task allocation sequence into a new inspection instruction including a waypoint sequence and a task time window, and sending the new inspection instruction to the UAV; After parsing the new inspection instruction, the drone updates the path planning of the onboard navigation system and executes the remaining inspection tasks according to the task time window.

8. The method according to claim 1, characterized in that In the step S3, The integrated equipment collects temperature, humidity and harmful gas concentration data in the tunnel in real time through the environmental sensing unit to generate 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, and if it detects that the temperature exceeds a safety threshold or the concentration of harmful gases exceeds the standard, the corresponding coordinates are marked as abnormal areas; The coordinates of the abnormal area are added to the preset path of the subsequent inspection task to collect environmental data of the abnormal area.

9. The method according to claim 1, characterized in that In the step S5, The integrated device discharges the heat generated by the wireless charging module and the signal relay module during operation to the outside of the tunnel through a heat dissipation system composed of a heat dissipation fan and a guide channel; The heat dissipation system monitors the internal temperature of the integrated device in real time through a temperature sensor and dynamically adjusts the speed of the heat dissipation fan according to the temperature value; If the internal temperature continues to exceed the set temperature threshold, the output power of the wireless charging module is reduced, and an overheating alarm signal including a device number and a temperature value is generated; After receiving the overheating alarm signal, the central management platform dispatches adjacent integrated equipment to take over the communication and charging tasks of the current UAV and triggers the equipment cooling maintenance process.

Images