Underground sewage plant inspection system based on unmanned aerial vehicle and method thereof

Abstract

The invention discloses an underground sewage plant inspection system based on an unmanned aerial vehicle and a method thereof, and relates to the technical field of unmanned aerial vehicle inspection. The unmanned aerial vehicle body is integrated with a data acquisition module, a motion module, an autonomous charging module, an intelligent alarm module, a three-dimensional scanning module, a space positioning sensor, a video data acquisition module, a toxic and harmful gas detection module, a temperature and humidity detection module, a sound sensor, a thermal imager and an autonomous positioning module. The system further comprises a lighting module, a communication interface module, a monitoring background and a charging dock. Automatic inspection of the unmanned aerial vehicle avoids the risk that inspection personnel enter a dangerous area, the personal safety of the inspection personnel is effectively guaranteed, meanwhile, by introducing the unmanned aerial vehicle technology and intelligent management, comprehensive, efficient and safe inspection of the underground sewage plant is achieved, the unmanned aerial vehicle system can rapidly traverse all corners of the underground sewage plant, and the inspection efficiency is improved. Data of equipment and pipelines are collected in real time, and the inspection efficiency and accuracy are improved.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) inspection technology, and in particular to an UAV-based inspection system and method for underground sewage treatment plants. Background Technology

[0002] As an important facility for urban sewage treatment, underground sewage treatment plants are characterized by large spaces, numerous equipment, and complex pipelines. These characteristics pose many challenges to the daily operation and maintenance management of underground sewage treatment plants, especially in inspection work. Although the traditional manual inspection method can meet the daily operation and maintenance needs of sewage treatment plants to a certain extent, its drawbacks are becoming increasingly apparent.

[0003] First, due to the vast space and complex equipment and pipelines of underground wastewater treatment plants, manual inspections are extremely labor-intensive. Inspectors need to traverse every corner, checking every piece of equipment and pipeline, which not only consumes a lot of manpower and time but is also relatively inefficient. Second, manual inspections have many blind spots. Due to the structural characteristics of underground wastewater treatment plants, many spaces, such as the narrow spaces between equipment rooms and upper areas, are difficult for humans to reach or observe, increasing the difficulty of inspection in these areas and even making effective inspection impossible. Third, the images and data from manual inspections are not traceable. Problems discovered during the inspection process need to be recorded manually, which not only increases the workload but also makes it impossible to guarantee the accuracy and completeness of the data. More importantly, there are certain personal safety hazards during manual inspections. Some enclosed spaces in underground wastewater treatment plants are at risk of leakage, especially underground spaces. Once a leakage occurs, it can easily cause the accumulation of toxic and harmful gases such as hydrogen sulfide, posing a serious threat to the personal safety of inspection personnel.

[0004] Although wheeled and rail-guided robots have seen some application in inspection technology in recent years, their applicability in underground wastewater treatment plants is limited. Due to the numerous steps and multi-layered structures in underground wastewater treatment plants, conventional wheeled and rail-guided robots cannot climb the steps and can only inspect equipment on the ground floor. They are inadequate for inspecting upper and lower levels, and cannot inspect pipelines and equipment on the upper and top layers of the structure. Therefore, there is a need to design an unmanned aerial vehicle (UAV)-based inspection system for underground wastewater treatment plants to address the aforementioned problems. Summary of the Invention

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] An inspection system for underground sewage treatment plants based on unmanned aerial vehicles (UAVs) includes a UAV body, which integrates a data acquisition module, a motion module, an autonomous charging module, an intelligent alarm module, a 3D scanning module, a spatial positioning sensor, a video data acquisition module, a toxic and harmful gas detection module, a temperature and humidity detection module, a sound sensor, a thermal imager, and an autonomous positioning module.

[0007] The output terminals of the three-dimensional scanning module, spatial positioning sensor, video data acquisition module, toxic and harmful gas detection module, temperature and humidity detection module, sound sensor and thermal imager are respectively connected to the input terminal of the data acquisition module, and are used to transmit detection or scanning data to the data acquisition module.

[0008] The output end of the data acquisition module is connected to the input end of the intelligent alarm module, and is used to transmit the acquired data to the intelligent alarm module for analysis and judgment.

[0009] The output of the autonomous positioning module is connected to the input of the motion module, and the output of the motion module is connected to the input of the data acquisition module. This module provides position guidance to the motion module and transmits the guidance data and motion trajectory back to the backend through the data acquisition module.

[0010] Furthermore, it also includes lighting modules, communication interface modules, a monitoring backend, and a charging dock station;

[0011] The output terminal of the UAV body is connected to the input terminal of the lighting module, which is used to control the working state of the lighting module;

[0012] The output end of the UAV body is connected to the input end of the communication interface module, and the output end of the communication interface module is connected to the input end of the monitoring backend, which is used to transmit various data of the UAV body and implement background monitoring.

[0013] The charging dock includes a drone docking bay and a wireless charging device. The drone docking bay is compatible with the wireless charging device. The output end of the autonomous charging module is connected to the input end of the communication interface module, and the output end of the communication interface module is connected to the input end of the wireless charging device, so that the drone body can dock in the drone docking bay for wireless charging.

[0014] Furthermore, the charging station is equipped with an IP65 protection rating and can communicate with the drone itself to automatically synchronize drone status data and all collected data.

[0015] It also has a module for communicating with the drone control platform, which is integrated into the monitoring backend. The drone control platform can remotely monitor the charging dock, view its status, and remotely set drone charging strategies.

[0016] Setting the drone charging strategy includes setting the charging time period and charging current; the drone docking cabin is a sealed cabin with dimensions matching the drone size. The drone docking cabin is equipped with an automatic door at the top, which is an upward-opening door. The automatic door is interlocked with the drone. When the drone approaches, the automatic door is sensed and opens automatically. After the drone enters, the automatic door closes automatically.

[0017] Furthermore, the monitoring backend can monitor on-site equipment information, the status of the drone itself, and the on-site environment in real time, receive real-time data transmitted by the drone, and remotely control the drone.

[0018] Furthermore, the drone itself and the monitoring backend use a wireless local area network or 5G to transmit data in real time.

[0019] The UAV body and the charging dock station use a wireless local area network interface for data transmission.

[0020] The charging dock station is connected to the monitoring backend via a fiber optic communication interface.

[0021] Furthermore, the lighting module is installed on the drone body. The lighting module adopts a diffuse reflection light source structure and converts the LED light source into uniform and soft light through an optical diffuser plate. This effectively avoids the problem of reflection and glare caused by strong light shining directly on the water surface and the smooth surface of the pipe, ensuring that the images captured by the video data acquisition module are clear and free of interference.

[0022] The lighting module integrates a remote control drive circuit, which supports two-way data interaction between the drone body's communication interface module and the monitoring backend. Operators can adjust the light source brightness and illumination angle in real time in the monitoring backend to adapt to the lighting needs of different areas of the underground sewage treatment plant.

[0023] The housing of the lighting module is made of waterproof and corrosion-resistant material, with a protection level of IP65, which can ensure stable operation in humid and corrosive gas environments.

[0024] Furthermore, the communication devices and cables of the inspection system are made of moisture-proof and corrosion-resistant materials, or are encapsulated and protected with moisture-proof and corrosion-resistant outer layers.

[0025] Furthermore, both the drone itself and the charging station are equipped with intelligent alarm modules, which automatically send alarm information when a fault, abnormality, or emergency is detected.

[0026] The intelligent alarm module includes: drone body fault alarm, inspection path alarm, charging dock station fault alarm, environmental anomaly alarm, intelligent identification anomaly alarm, and platform anomaly alarm.

[0027] The drone's own fault alarms include: battery power, drive module, detection equipment, remote control and telemetry signals, drone disconnection, and camera obstruction;

[0028] Inspection path alarms include: when an obstacle occurs during the inspection process, when the path cannot be passed, when an alternative path is automatically switched, and when a collision occurs.

[0029] Charging dock station fault alarms include: the dock station malfunctions and cannot charge, and communication failure with the drone itself or the backend.

[0030] Environmental anomaly alarms include: equipped with an H2S detection module and a multi-probe interface module, which will trigger an alarm when an anomaly is detected;

[0031] Intelligent anomaly detection alarm: An alarm is triggered when abnormalities are detected in equipment, personnel, or pipelines.

[0032] Furthermore, the drone also includes an image recognition module, a data comparison module, and a vibration monitoring module, used for identification of various inspection scenarios;

[0033] The image recognition module is integrated into the data acquisition module of the UAV body. It adopts a deep learning convolutional neural network architecture and can intelligently analyze the real-time images transmitted by the video data acquisition module. The image recognition module has built-in equipment anomaly recognition, pipeline defect detection and personnel intrusion warning.

[0034] Equipment anomaly detection: Real-time assessment of equipment operating status through contour matching and motion trajectory analysis;

[0035] Pipeline defect detection: Using edge detection and image segmentation technology, cracks, corrosion and blockage defects are identified on the inner wall of sewage pipes. Millimeter-level cracks can be located, and a heat map of defect location is generated by combining spatial data from the 3D scanning module.

[0036] Personnel intrusion warning: The alarm is automatically triggered when personnel activity is detected in unauthorized areas through human posture recognition algorithm. At the same time, it is linked with thermal imager to distinguish between personnel and equipment heat sources, reducing the false alarm rate.

[0037] This invention also provides a method for inspecting underground sewage treatment plants based on unmanned aerial vehicles (UAVs), comprising the following steps:

[0038] S1. System initialization and self-test: After the human-machine body is started, the autonomous charging module detects the battery power, and the data acquisition module simultaneously activates the 3D scanning module and the spatial positioning sensor detection module to perform a hardware status self-test.

[0039] The communication interface module establishes a wireless LAN or 5G connection with the monitoring backend, transmits device initialization data, and enters the inspection state after confirming that each module is operating normally.

[0040] S2. UAV Takeoff and Path Planning: The autonomous positioning module, combined with the spatial positioning sensor, generates initial positioning coordinates, and the motion module drives the UAV to take off along the preset route.

[0041] During flight, the 3D scanning module constructs a 3D map of the underground space in real time, and the autonomous positioning module corrects the flight trajectory to ensure that the flight proceeds to the preprocessing unit according to the planned path.

[0042] S3. Preprocessing unit inspection: When the drone arrives at the preprocessing unit, the lighting module turns on the diffuse light source, and the video data acquisition module captures on-site images.

[0043] The image recognition module detects the opening and closing status of the coarse grid grab bucket through contour matching and uses an oil stain recognition algorithm to determine the oil pipe leakage situation.

[0044] Sound sensors collect the operating sounds of the press and sand separator, and compare them with a reference audio to identify abnormalities in the residue.

[0045] The temperature and humidity detection module works with the thermal imager to monitor the temperature in the pump pit area, and combines video analysis to detect water overflow and the condition of garbage and foam on the pool surface.

[0046] The data acquisition module synchronizes mechanical instrument readings and control cabinet alarm signal data to the monitoring backend;

[0047] S4. Inspection of the biochemical treatment unit: The drone enters the biochemical treatment area according to the planned path, the sound sensor identifies abnormal noises from the fan, and the vibration monitoring module detects the vibration frequency of the equipment during operation.

[0048] The toxic and harmful gas detection module monitors the concentration of H2S and NH3 gases in real time, while the temperature and humidity detection module records environmental parameters.

[0049] The image recognition module analyzes the pressure difference of the inlet filter through edge detection and combines it with a thermal imager to locate the heat source of gas leakage.

[0050] The video data acquisition module captures images of the pool surface, identifies the distribution of garbage and foam, and synchronizes the data to the monitoring backend for anomaly analysis.

[0051] S5. Deep processing unit inspection: The drone enters the deep processing unit, and the 3D scanning module and video data acquisition module work together to monitor the running trajectory of the secondary sedimentation tank sludge scraper and the height of the mud layer on the tank surface.

[0052] The image recognition module analyzes the clarity of the effluent from the high-efficiency sedimentation tank by measuring the light transmittance of the water body and detects the cleanliness of the inclined tube;

[0053] Thermal imagers scan valves and pipes in denitrification filters to identify hotspots for leaks and spills.

[0054] The video data acquisition module captures the screen parameters of the membrane tank blower, and the vibration monitoring module analyzes the operating stability of the blower.

[0055] S6. Data transmission and automatic charging: During the inspection, the drone body transmits data to the monitoring backend in real time through the communication interface module, and the charging station receives status information synchronously.

[0056] When the battery level is lower than the preset threshold, the autonomous charging module triggers a return-to-home command, the drone docking cabin automatically opens, and the drone enters and starts wireless charging.

[0057] The charging station synchronizes all data collected by the drone with the monitoring backend via fiber optic cable, including 3D scanning models, images and detection parameters;

[0058] S7. Abnormal Alarm and Data Archiving: The intelligent alarm module performs real-time analysis of the collected data. When it detects abnormalities such as battery abnormality, equipment failure due to camera obstruction, collision or impassable path obstacles, excessive environmental parameters or personnel intrusion, or pipe cracks, it automatically sends an alarm signal to the monitoring backend.

[0059] The data comparison module compares real-time data with historical benchmark values ​​to generate equipment status trend reports. The defect detection results of the image recognition module are fused with 3D scanning data to form a visualized inspection file.

[0060] The monitoring backend triggers the corresponding handling process based on the alarm level, and archives and stores the complete inspection data for subsequent analysis and optimization.

[0061] Compared with existing technologies, it has the following beneficial effects:

[0062] Automated inspections using drones eliminate the risk of personnel entering hazardous areas, effectively ensuring their safety. Furthermore, the introduction of drone technology and intelligent management enables comprehensive, efficient, and safe inspections of underground wastewater treatment plants. The drone system can quickly traverse every corner of the plant, collecting real-time status data on equipment and pipelines, significantly improving inspection efficiency and accuracy. Its flexible flight capabilities and omnidirectional coverage allow it to easily access areas difficult for humans to reach, effectively reducing blind spots. The monitoring backend receives and stores data transmitted by the drone system in real time, ensuring data traceability and providing strong support for subsequent operation and maintenance management. Integrating an intelligent alarm module and monitoring backend enables remote monitoring and control of the drone system, enhancing the system's intelligent management level.

[0063] Through data acquisition modules, 3D scanning modules, intelligent alarm modules, and a monitoring backend, the system achieves real-time monitoring of the operating status and environmental parameters of underground wastewater treatment equipment and provides automatic alarms for anomalies. The data acquisition module integrates data from multiple sensors, the 3D scanning module constructs a spatial model, the intelligent alarm module analyzes data to trigger early warnings, and the monitoring backend enables remote visual management, forming a closed loop of data acquisition, analysis, alarm, and monitoring. This replaces blind spots in manual inspections and improves the timeliness and accuracy of fault detection.

[0064] Through a charging dock, autonomous charging module, lighting module, and communication interface module, the system achieves autonomous flight, adaptability to complex environments, and stable data transmission for drones. The charging dock supports wireless charging and data synchronization, the autonomous charging module enables automatic return to base when the battery is low, the lighting module solves the problems of underground reflection and corrosion through diffuse reflection light sources and IP65 protection, and the communication interface module ensures data interaction between multiple devices, ensuring continuous inspection and environmental adaptability.

[0065] By using S1 system initialization and self-test, S6 data transmission and automatic charging, and S7 anomaly alarm and data archiving, the entire inspection process is automated and data is traceable. Initialization ensures that the equipment is in normal condition, automatic charging maintains continuous operation, and anomaly alarm linkage and data archiving form a closed-loop management system. This reduces manual intervention and supports operation and maintenance optimization through historical data comparison and visualized archives, thereby improving the inspection efficiency and management accuracy of underground wastewater treatment plants. Attached Figure Description

[0066] Figure 1 This is a schematic diagram of the system architecture of the UAV-based underground sewage treatment plant inspection system of the present invention;

[0067] Figure 2 This is a schematic diagram of the process of the unmanned aerial vehicle (UAV)-based inspection method for underground sewage treatment plants according to the present invention.

[0068] The numbers in the diagram are:

[0069] 1. Drone body; 2. Lighting module; 3. Communication interface module; 4. Charging dock; 5. Monitoring backend; 6. Data acquisition module; 7. Motion module; 8. Autonomous charging module; 9. Intelligent alarm module; 10. 3D scanning module; 11. Spatial positioning sensor; 12. Video data acquisition module; 13. Toxic and harmful gas detection module; 14. Temperature and humidity detection module; 15. Sound sensor; 16. Thermal imager; 17. Autonomous positioning module; 18. Drone docking bay; 19. Wireless charging equipment. Detailed Implementation

[0070] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0071] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0072] Please see Figure 1 The present invention provides a technical solution: an underground sewage treatment plant inspection system based on unmanned aerial vehicles (UAVs), including a UAV body 1. The UAV body 1 integrates a data acquisition module 6, a motion module 7, an autonomous charging module 8, an intelligent alarm module 9, a three-dimensional scanning module 10, a spatial positioning sensor 11, a video data acquisition module 12, a toxic and harmful gas detection module 13, a temperature and humidity detection module 14, a sound sensor 15, a thermal imager 16, and an autonomous positioning module 17.

[0073] The output terminals of the 3D scanning module 10, the spatial positioning sensor 11, the video data acquisition module 12, the toxic and harmful gas detection module 13, the temperature and humidity detection module 14, the sound sensor 15, and the thermal imager 16 are respectively connected to the input terminal of the data acquisition module 6 to transmit detection or scanning data to the data acquisition module 6.

[0074] The output of the data acquisition module 6 is connected to the input of the intelligent alarm module 9, and is used to transmit the acquired data to the intelligent alarm module 9 for analysis and judgment.

[0075] The output of the autonomous positioning module 17 is connected to the input of the motion module 7, and the output of the motion module 7 is connected to the input of the data acquisition module 6. This module provides position guidance to the motion module 7 and transmits the guidance data and motion trajectory back to the back end through the data acquisition module 6.

[0076] It also includes lighting module 2, communication interface module 3, monitoring backend 5, and charging dock station 4;

[0077] The output end of the UAV body 1 is connected to the input end of the lighting module 2 to control the working state of the lighting module 2;

[0078] The output end of the UAV body 1 is connected to the input end of the communication interface module 3, and the output end of the communication interface module 3 is connected to the input end of the monitoring backend 5. This is used to transmit various data of the UAV body 1 and implement backend monitoring, building an efficient data bridge between the UAV and the backend, enabling maintenance personnel to grasp the UAV status and inspection data in real time, assisting in timely decision-making and precise control, and greatly improving the inspection efficiency and reliability of underground sewage treatment plants.

[0079] The charging dock 4 includes a drone docking bay 18 and a wireless charging device 19. The drone docking bay 18 is compatible with the wireless charging device 19. The output end of the autonomous charging module 8 is connected to the input end of the communication interface module 3, and the output end of the communication interface module 3 is connected to the input end of the wireless charging device 19. This allows the drone body 1 to dock in the drone docking bay 18 for wireless charging. With the help of wireless charging and intelligent docking design, the drone can autonomously replenish its flight time without the need for tedious manual cable plugging and unplugging, greatly reducing the workload of manual maintenance and ensuring the continuity and efficiency of inspection work.

[0080] The charging dock station 4 is equipped with an IP65 protection rating and can communicate with the drone body 1 to automatically synchronize the drone's status data and all collected data. The high IP65 protection rating can withstand the humid and corrosive environment of the underground sewage treatment plant, ensuring the stable operation of the dock station. At the same time, automatic data synchronization provides a solid guarantee for the integrity and real-time nature of the inspection data, which is convenient for traceability and analysis.

[0081] It also has a module for communicating with the drone control platform, which is integrated into the monitoring backend 5. The drone control platform can remotely monitor the charging dock, view its status, and remotely set the drone charging strategy.

[0082] Setting up a drone charging strategy includes setting the charging time period and charging current. The drone docking bay 18 is a sealed cabin with dimensions matching the drone's size. The drone docking bay 18 has an automatic door at the top, which is an upward-opening door. The automatic door is interlocked with the drone. When the drone approaches, the automatic door opens automatically. After the drone enters, the automatic door closes automatically, enabling remote monitoring and flexible configuration of the charging strategy. Maintenance personnel can adjust the charging plan according to actual needs, optimize drone usage efficiency, and monitor the docking station's operating status in real time to ensure stable system operation.

[0083] The monitoring backend 5 can monitor the information of on-site equipment, the status of the drone body 1 and the on-site environment in real time, receive real-time data transmitted by the drone system, and remotely control the drone system. The sealed cabin and precise size design not only ensure the charging safety of the drone, but also avoid interference from external impurities. The automatic door interlocking mechanism enables unattended intelligent docking, improving the convenience of use and the safety of the equipment.

[0084] The drone body 1 and the monitoring backend 5 use wireless local area network or 5G to transmit data in real time, and have comprehensive real-time monitoring and remote control functions. This allows maintenance personnel to be as if they were on-site, quickly perceive equipment abnormalities and environmental changes, and intervene remotely in a timely manner, effectively improving the timeliness and accuracy of inspection and management of underground sewage treatment plants.

[0085] The drone body 1 and the charging dock station 4 use a wireless local area network interface for data transmission. This interface ensures smooth interaction of status information between the drone and the charging dock station, ensuring that the drone can accurately receive charging instructions and complete charging operations in a timely manner, thereby improving the intelligent level of drone endurance management.

[0086] The charging dock station 4 and the monitoring backend 5 are connected via a fiber optic communication interface. Fiber optic communication has the characteristics of high speed, large capacity and strong anti-interference, which can realize the stable transmission of large amounts of data between the dock station and the backend, providing reliable support for the backend to fully grasp the inspection data.

[0087] The lighting module 2 is installed on the drone body 1. The lighting module 2 adopts a diffuse reflection light source structure. The LED light source is converted into uniform and soft light through an optical diffuser plate, which effectively avoids the problem of reflection and glare caused by strong light shining directly on the water surface and smooth surface of the pipe. This ensures that the images captured by the video data acquisition module 12 are clear and free of interference. The diffuse reflection light source cleverly solves the problem of reflection on complex surfaces in underground sewage treatment plants, making the captured images clearly present the details of the equipment, providing inspection personnel with accurate and intuitive visual information, and improving the quality of inspection.

[0088] The lighting module 2 integrates a remote control drive circuit, which supports two-way data interaction between the communication interface module 3 of the drone body 1 and the monitoring backend 5. Operators can adjust the brightness and illumination angle of the light source in real time on the monitoring backend 5 to adapt to the lighting needs of different areas of the underground sewage treatment plant. The remotely adjustable light source gives the inspection operation a high degree of flexibility and can quickly adapt to the best lighting according to different scenarios, meet the diverse lighting needs of inspection in complex environments, and improve the efficiency and accuracy of inspection.

[0089] The housing of lighting module 2 is made of waterproof and corrosion-resistant material with an IP65 protection rating. It can work stably in humid and corrosive gas environments. The IP65 waterproof and corrosion-resistant housing provides a solid foundation for the stable operation of the lighting module in the harsh environment of underground sewage treatment plants, extends the service life of the equipment, reduces maintenance costs, and ensures the continuous reliability of inspection lighting work.

[0090] The communication devices and cables of the inspection system are made of moisture-proof and corrosion-resistant materials, or are encapsulated and protected with moisture-proof and corrosion-resistant outer layers. The moisture-proof and corrosion-resistant treatment effectively prevents the communication lines from being corroded by the harsh environment of the sewage treatment plant, reduces the probability of line failure, ensures the stability and continuity of data communication, and ensures the stable operation of the inspection system.

[0091] Both the drone body 1 and the charging dock station 4 are equipped with intelligent alarm modules 9, which automatically send alarm information when a fault, abnormality or emergency is detected. The multi-terminal intelligent alarm modules build an all-round security defense line, which can detect abnormalities at the first time, buy valuable time for maintenance personnel, and greatly improve the security and stability of the inspection system.

[0092] The intelligent alarm module 9 includes: drone body 1 fault alarm, inspection path alarm, charging dock station 4 fault alarm, environmental anomaly alarm, intelligent identification anomaly alarm, and platform anomaly alarm. This multi-dimensional alarm system comprehensively covers potential risks in all aspects of the inspection process, from equipment failure to environmental changes and path obstacles, ensuring that no anomaly can be hidden and guaranteeing the smooth progress of the inspection work.

[0093] The drone body fault alarm includes: battery power, drive module, detection equipment, remote control and telemetry signal, drone disconnection, camera obstruction, accurately focusing on various key components and communication faults of the drone, helping maintenance personnel to quickly locate the root cause of the problem, quickly carry out maintenance work, and reduce downtime;

[0094] The inspection path alarm includes: when an obstacle occurs during the inspection process, when the path cannot be passed, when an alternative path is automatically switched, and when a collision occurs. The path abnormality alarm and automatic switching mechanism ensure that the drone inspection path is always unobstructed, effectively avoids obstacles, reduces human intervention, and improves the autonomy and reliability of the inspection task execution.

[0095] The charging dock station 4 fault alarm includes: the dock station malfunctions and cannot charge, communication failure with the drone body 1 or the backend. It monitors the operation status of the charging dock station in real time and will immediately alarm once a fault occurs to prevent the drone's flight time from being interrupted due to dock station problems and ensure the normal operation of the inspection system.

[0096] Environmental anomaly alarms include: equipped with an H2S detection module and a multi-probe interface module, which will alarm when an anomaly is detected. For high-risk toxic gas environments in underground sewage treatment plants, it can promptly detect abnormal concentrations of gases such as H2S, providing a strong early warning to ensure personnel safety and stable equipment operation.

[0097] Intelligent anomaly identification alarm: When abnormalities in equipment, personnel, and pipelines are identified, an alarm is triggered. With the help of AI intelligent identification technology, it can accurately detect abnormal situations such as equipment failure, personnel intrusion, and pipeline defects, so as to realize intelligent early warning and improve inspection efficiency and safety prevention level.

[0098] The drone system also includes an image recognition module, a data comparison module, and a vibration monitoring module, which are used to identify various inspection scenarios. The multiple modules work together to conduct in-depth analysis of the inspection scenarios from multiple dimensions such as vision, data, and vibration, so as to achieve intelligent and accurate identification and provide strong support for efficient inspection and fault diagnosis.

[0099] The image recognition module is integrated into the data acquisition module 6 of the UAV body 1. It adopts a deep learning convolutional neural network architecture and can intelligently analyze the real-time images transmitted by the video data acquisition module 12. The image recognition module has built-in equipment anomaly recognition, pipeline defect detection and personnel intrusion warning. The deep learning algorithm gives the image recognition module powerful analysis capabilities, accurately detects equipment, pipeline and personnel anomalies, and provides efficient and intelligent visual monitoring means for the inspection of underground sewage treatment plants.

[0100] Equipment anomaly identification: Through contour matching and motion trajectory analysis, the equipment operating status is determined in real time. Based on advanced vision algorithms, the equipment operating status is evaluated in real time and accurately, replacing traditional manual inspections and improving the accuracy and timeliness of equipment status monitoring.

[0101] Pipeline defect detection: Utilizing edge detection and image segmentation technology, cracks, corrosion, and blockage defects are identified on the inner wall of sewage pipes. Millimeter-level cracks can be located, and a heat map of the defect location is generated by combining spatial data from the 3D scanning module 10. The millimeter-level precision of pipeline defect location, combined with the visualization of the heat map, provides detailed and accurate data for pipeline maintenance, helping to make efficient maintenance decisions.

[0102] Personnel intrusion warning: Through human posture recognition algorithm, an alarm is automatically triggered when personnel activity is detected in unauthorized areas. At the same time, it is linked with thermal imager 16 to distinguish between personnel and equipment heat sources, reducing the false alarm rate. By integrating human posture recognition and thermal imaging technology, it can accurately identify unauthorized personnel intrusion into unauthorized areas, reduce false alarms, and enhance the safety protection of sewage treatment plants.

[0103] Please see Figures 1-2 An inspection method for underground wastewater treatment plants based on a drone system, applicable to an underground wastewater treatment plant inspection system, includes the following steps:

[0104] S1. System initialization and self-test: After the human-machine body 1 is started, the autonomous charging module 8 detects the battery power, and the data acquisition module 6 simultaneously activates the three-dimensional scanning module 10 and the spatial positioning sensor 11 to perform hardware status self-test. The comprehensive hardware self-test at startup helps to identify potential faults in advance and ensures that each module operates normally, laying a solid foundation for the smooth progress of subsequent inspection tasks.

[0105] Communication interface module 3 establishes a wireless LAN or 5G connection with the monitoring backend 5, transmits device initialization data, and enters the inspection state after confirming that each module is operating normally. It quickly establishes a stable communication connection and transmits initialization data, enabling the system to quickly access the management platform and be ready to carry out inspection work at any time, thus improving response speed.

[0106] S2. UAV takeoff and path planning: The autonomous positioning module 17, combined with the spatial positioning sensor 11, generates the initial positioning coordinates. The motion module 7 drives the UAV to take off along the preset route. The precise positioning and preset route takeoff mechanism ensures that the UAV flies along the planned path from the beginning, ensuring the orderly start of the inspection task and improving the inspection efficiency.

[0107] During flight, the 3D scanning module 10 constructs a 3D map of the underground space in real time, and the autonomous positioning module 17 corrects the flight trajectory to ensure that the drone travels to the preprocessing unit according to the planned path. The real-time construction of the 3D map and the trajectory correction help the drone to always fly along the optimal path in the complex underground environment, accurately reach each inspection area, and reduce flight errors.

[0108] S3. Pre-processing unit inspection: When the drone arrives at the pre-processing unit, the lighting module 2 turns on the diffuse reflection light source, and the video data acquisition module 12 captures on-site images. The lighting and image acquisition work together to clearly present the operation and environmental conditions of the pre-processing unit equipment, providing the inspection personnel with intuitive and accurate on-site information.

[0109] The image recognition module detects the opening and closing status of the coarse screen grab bucket through contour matching, uses oil stain recognition algorithm to determine oil pipe leakage, and employs advanced vision algorithm to accurately identify the key status of the coarse screen equipment and potential oil pipe leakage, thus efficiently completing the inspection of key equipment in the pretreatment unit and improving inspection accuracy.

[0110] The sound sensor 15 collects the operating sounds of the press and sand separator, compares them with the reference audio to identify abnormalities in the residue, and uses voiceprint analysis technology to accurately determine abnormalities in the operation of equipment such as the press in a non-contact manner, reducing errors in manual listening and improving the reliability of equipment abnormality detection.

[0111] The temperature and humidity detection module 14 works with the thermal imager 16 to monitor the temperature of the pump pit area. Combined with video analysis, it monitors water overflow and the situation of garbage and foam on the surface of the pool. The fusion of multiple sensors comprehensively monitors the environmental parameters and abnormal phenomena of the pump pit, providing data support for the stable operation of the pretreatment process and ensuring the sewage treatment effect.

[0112] Data acquisition module 6 synchronizes mechanical instrument readings and control cabinet alarm signal data to the monitoring backend 5, timely synchronizing key equipment data and alarm signals, providing accurate and detailed data for backend maintenance personnel, and facilitating rapid decision-making and processing;

[0113] S4. Inspection of the biochemical treatment unit: The drone enters the biochemical treatment area according to the planned path. The sound sensor 15 identifies abnormal noises from the fan, and the vibration monitoring module detects the vibration frequency of the equipment. The sound and vibration joint detection technology accurately captures abnormal operation of equipment such as fans, provides early warning of mechanical failures, and ensures the stable operation of key biochemical treatment equipment.

[0114] The toxic and harmful gas detection module 13 monitors the concentration of H2S and NH3 gases in real time, and the temperature and humidity detection module 14 records environmental parameters. Targeted gas and environmental parameter monitoring enables real-time control of the safety and process environment of the biochemical treatment area, providing data support for production safety and process optimization.

[0115] The image recognition module analyzes the pressure difference of the inlet filter through edge detection, and combines it with the thermal imager to locate the heat source of gas leakage. By combining vision and thermal imaging, it can quickly locate abnormal filter pressure difference and gas leakage points, efficiently solve potential equipment failures, and improve the efficiency of inspection work.

[0116] The video data acquisition module 12 captures images of the pool surface, identifies the distribution of garbage and foam, and synchronizes the data to the monitoring backend 5 for anomaly analysis. The intelligent analysis and data synchronization of the pool surface images provide visualized data for the evaluation of the biochemical treatment effect and the investigation of anomalies, helping to improve the quality of sewage treatment.

[0117] S5. Inspection of the deep processing unit: The drone enters the deep processing unit. The 3D scanning module 10 and the video data acquisition module 12 work together to monitor the running trajectory of the sludge scraper in the secondary sedimentation tank and the height of the mud layer on the surface of the tank. The combination of 3D scanning and image acquisition accurately monitors the operation of the sludge scraper and the state of the mud layer, providing key data support for the stable operation of the deep processing process.

[0118] The image recognition module analyzes the clarity of the effluent from the high-efficiency sedimentation tank by measuring the light transmittance of the water and detects the cleanliness of the inclined tube. Based on optical principles, the image recognition analysis accurately assesses the treatment effect of the high-efficiency sedimentation tank and the cleanliness of the equipment, helping to optimize the deep treatment process.

[0119] The thermal imager scans the valves and pipelines of the denitrification filter to identify hot spots of leakage, and uses thermal imaging technology to quickly locate potential leaks in valves and pipelines, providing accurate location information for equipment maintenance and reducing the risk of equipment failure.

[0120] The video data acquisition module 12 captures the screen parameters of the membrane tank blower, the vibration monitoring module analyzes the operating stability of the blower, and multiple methods are used to monitor the operating status of the membrane tank blower, providing comprehensive data support for the stable operation of key equipment in the deep treatment unit and ensuring the smooth flow of the sewage treatment process.

[0121] S6. Data transmission and automatic charging: During the inspection, the UAV body 1 transmits data to the monitoring backend 5 in real time through the communication interface module 3. The charging dock station 4 receives the status information synchronously. Real-time data transmission ensures that the backend can obtain the inspection results in a timely manner. The synchronous status information of the dock station provides a basis for the UAV's endurance management and ensures the efficient and collaborative operation of the system.

[0122] When the battery level is lower than the preset threshold, the autonomous charging module 8 triggers a return command, the drone docking cabin 18 automatically opens, and the drone enters and starts wireless charging. The intelligent battery monitoring and automatic charging mechanism ensures that the drone has no worries about its battery life, realizes unattended autonomous charging, and improves the automation level of the inspection system.

[0123] The charging station 4 synchronizes all data collected by the drone with the monitoring backend 5 via fiber optic cable, including 3D scanning models, images and detection parameters. The high-speed fiber optic transmission enables complete synchronization of all data, providing detailed information for the backend to conduct comprehensive and in-depth analysis of the inspection situation, and assisting in accurate decision-making and management.

[0124] S7. Anomaly Alarm and Data Archiving: The intelligent alarm module 9 performs real-time analysis of the collected data. When it detects abnormalities such as battery abnormalities, equipment failure due to camera obstruction, collisions or impassable path obstacles, excessive environmental parameters or personnel intrusion, or intelligent identification abnormalities such as pipe cracks, it automatically sends an alarm signal to the monitoring backend 5. The intelligent alarm module screens anomalies in real time and quickly alarms the backend, giving maintenance personnel valuable time to deal with problems in a timely manner and ensuring inspection safety.

[0125] The data comparison module compares real-time data with historical benchmark values ​​to generate equipment status trend reports. The defect detection results of the image recognition module are fused with 3D scanning data to form a visualized inspection archive. The data comparison and fusion generate a comprehensive visualized archive, providing rich historical data references for equipment operation and maintenance and inspection optimization, and helping to improve management level.

[0126] The monitoring backend 5 triggers corresponding handling procedures based on the alarm level, and archives and stores complete inspection data for subsequent analysis and optimization. The hierarchical handling and data archiving enable efficient handling of inspection issues and data accumulation and utilization, laying the foundation for continuous optimization and upgrading of the underground sewage treatment plant inspection system.

[0127] This invention provides an electronic device that may include a processor 401, a communication interface, a memory, and a bus. The processor, communication interface, and memory communicate with each other via the bus. The communication interface can be used for information transmission within the electronic device. The processor can invoke logical instructions from the memory to execute a UAV-based underground wastewater treatment plant inspection method.

[0128] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the above-described method embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0129] On the other hand, embodiments of the present invention also provide a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, is implemented to perform a UAV-based underground wastewater treatment plant inspection method.

[0130] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0131] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0132] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Identical components are represented by the same reference numerals. Therefore, all equivalent changes made to the structure, shape, and principle of this application should be covered within the scope of protection of this application.

Claims

1. An inspection system for underground sewage treatment plants based on unmanned aerial vehicles (UAVs), comprising the UAV body (1), characterized in that: The UAV body (1) integrates a data acquisition module (6), a motion module (7), an autonomous charging module (8), an intelligent alarm module (9), a three-dimensional scanning module (10), a spatial positioning sensor (11), a video data acquisition module (12), a toxic and harmful gas detection module (13), a temperature and humidity detection module (14), a sound sensor (15), a thermal imager (16), and an autonomous positioning module (17). The output terminals of the three-dimensional scanning module (10), spatial positioning sensor (11), video data acquisition module (12), toxic and harmful gas detection module (13), temperature and humidity detection module (14), sound sensor (15) and thermal imager (16) are respectively connected to the input terminal of the data acquisition module (6) for transmitting detection or scanning data to the data acquisition module (6); The output end of the data acquisition module (6) is connected to the input end of the intelligent alarm module (9) and is used to transmit the acquired data to the intelligent alarm module (9) for analysis and judgment. The output of the autonomous positioning module (17) is connected to the input of the motion module (7), and the output of the motion module (7) is connected to the input of the data acquisition module (6). The autonomous positioning module (17) provides position guidance to the motion module (7) and transmits the guidance data and motion trajectory back to the back end through the data acquisition module (6).

2. The UAV-based underground sewage treatment plant inspection system according to claim 1, characterized in that: It also includes a lighting module (2), a communication interface module (3), a monitoring backend (5), and a charging dock (4); The output end of the UAV body (1) is connected to the input end of the lighting module (2) to control the working state of the lighting module (2); The output end of the UAV body (1) is connected to the input end of the communication interface module (3), and the output end of the communication interface module (3) is connected to the input end of the monitoring background (5) for transmitting various data of the UAV body (1) and implementing background monitoring. The charging station (4) includes a drone docking cabin (18) and a wireless charging device (19). The drone docking cabin (18) is adapted to the wireless charging device (19). The output end of the autonomous charging module (8) is connected to the input end of the communication interface module (3). The output end of the communication interface module (3) is connected to the input end of the wireless charging device (19), so that the drone body (1) can dock in the drone docking cabin (18) for wireless charging.

3. The UAV-based underground sewage treatment plant inspection system according to claim 1, characterized in that: The charging station (4) is equipped with an IP65 protection rating and can communicate with the UAV body (1) to automatically synchronize UAV status data and all collected data. It also has a module for communicating with the drone control platform. The drone control platform is integrated into the monitoring backend (5). The drone control platform can remotely monitor the charging dock, view its status, and remotely set the drone charging strategy. Setting the drone charging strategy includes setting the charging time period and charging current; the drone docking cabin (18) is a sealed cabin with dimensions matching the drone size. The drone docking cabin (18) has an automatic door on the top, which is an upward-opening door. The automatic door is interlocked with the drone. When the drone approaches, the automatic door is automatically opened. After the drone enters, the automatic door closes.

4. The UAV-based underground sewage treatment plant inspection system according to claim 1, characterized in that: The UAV body (1) and the monitoring backend (5) transmit data in real time via wireless local area network or 5G. The UAV body (1) and the charging dock (4) use a wireless local area network interface for data transmission. The charging dock station (4) and the monitoring backend (5) are connected via an optical fiber communication interface.

5. The UAV-based underground sewage treatment plant inspection system according to claim 1, characterized in that: The lighting module (2) is installed on the drone body (1). The lighting module (2) adopts a diffuse reflection light source structure. The LED light source is converted into uniform and soft light through an optical diffuser plate, which effectively avoids the problem of reflection and glare caused by strong light shining directly on the water surface and the smooth surface of the pipe, and ensures that the video data acquisition module (12) captures clear and interference-free images. The lighting module (2) integrates a remote control drive circuit, which supports two-way data interaction between the communication interface module (3) of the UAV body (1) and the monitoring backend (5). Operators can adjust the brightness and illumination angle of the light source in real time in the monitoring backend (5) to adapt to the lighting needs of different areas of the underground sewage treatment plant. The housing of the lighting module (2) is made of waterproof and corrosion resistant material, with a protection level of IP65, and can work stably in humid and corrosive gas environments.

6. The UAV-based underground sewage treatment plant inspection system according to claim 2, characterized in that: Both the UAV body (1) and the charging station (4) are equipped with an intelligent alarm module (9), which automatically sends alarm information when a fault, abnormality or emergency is detected. The intelligent alarm module (9) includes: drone body (1) fault alarm, inspection path alarm, charging dock (4) fault alarm, environmental anomaly alarm, intelligent identification anomaly alarm and platform anomaly alarm. The fault alarms of the UAV body (1) include: battery power, drive module, detection equipment, remote control and telemetry signal, UAV disconnection, and camera obstruction; Inspection path alarms include: when an obstacle occurs during the inspection process, when the path cannot be passed, when an alternative path is automatically switched, and when a collision occurs. The charging dock station (4) fault alarms include: the dock station malfunctions and cannot charge, or communication failure with the drone body (1) or the backend. Environmental anomaly alarms include: equipped with an H2S detection module and a multi-probe interface module, which will trigger an alarm when an anomaly is detected; Intelligent anomaly detection alarm: An alarm is triggered when abnormalities are detected in equipment, personnel, or pipelines.

7. The UAV-based underground sewage treatment plant inspection system according to claim 1, characterized in that: The drone system also includes an image recognition module, a data comparison module, and a vibration monitoring module, which are used to identify various inspection scenarios; The image recognition module is integrated into the data acquisition module (6) of the UAV body (1). It adopts a deep learning convolutional neural network architecture and can intelligently analyze the real-time images transmitted by the video data acquisition module (12). The image recognition module has built-in equipment anomaly recognition, pipeline defect detection and personnel intrusion warning. Equipment anomaly detection: Real-time assessment of equipment operating status through contour matching and motion trajectory analysis; Pipeline defect detection: Using edge detection and image segmentation technology, cracks, corrosion and blockage defects are identified on the inner wall of sewage pipes. Millimeter-level cracks can be located, and a heat map of the defect location is generated by combining the spatial data of the three-dimensional scanning module (10). Personnel intrusion warning: When personnel activity is detected in an unauthorized area through human posture recognition algorithm, an alarm is automatically triggered. At the same time, the thermal imager (16) is linked to distinguish between personnel and equipment heat sources to reduce the false alarm rate.

8. A method for inspecting underground wastewater treatment plants based on unmanned aerial vehicles (UAVs), applied to the UAV-based underground wastewater treatment plant inspection system described in any one of claims 1-7, characterized in that: The following usage steps are included: S1. System initialization and self-test: After the human-machine body (1) is started, the autonomous charging module (8) detects the battery power, and the data acquisition module (6) simultaneously activates the three-dimensional scanning module (10) and the spatial positioning sensor (11) detection module to perform hardware status self-test. The communication interface module (3) establishes a wireless local area network or 5G connection with the monitoring backend (5), transmits the device initialization data, and enters the inspection state after confirming that each module is running normally. S2. UAV takeoff and path planning: The autonomous positioning module (17) generates initial positioning coordinates in conjunction with the spatial positioning sensor (11), and the motion module (7) drives the UAV to take off along the preset route; During flight, the 3D scanning module (10) constructs a 3D map of the underground space in real time, and the autonomous positioning module (17) corrects the flight trajectory to ensure that the preprocessing unit is reached according to the planned path. S3, Preprocessing Unit Inspection: When the drone arrives at the preprocessing unit, the lighting module (2) turns on the diffuse light source, and the video data acquisition module (12) captures on-site images; The image recognition module detects the opening and closing status of the coarse grid grab bucket through contour matching and uses an oil stain recognition algorithm to determine the oil pipe leakage situation. The sound sensor (15) collects the operating sound of the press and sand separator, and compares it with the reference audio to identify abnormalities in the residue; The temperature and humidity detection module (14) works with the thermal imager (16) to monitor the temperature of the pump pit area and combine video analysis to analyze the overflow of water and the situation of garbage and foam on the pool surface; The data acquisition module (6) synchronizes the mechanical instrument readings and control cabinet alarm signal data to the monitoring backend (5); S4. Inspection of the biochemical treatment unit: The drone enters the biochemical treatment area according to the path plan, the sound sensor (15) identifies the abnormal noise of the fan, and the vibration monitoring module detects the vibration frequency of the equipment operation. The toxic and harmful gas detection module (13) monitors the concentration of H2S and NH3 gases in real time, and the temperature and humidity detection module (14) records environmental parameters. The image recognition module analyzes the pressure difference of the inlet filter through edge detection and uses the thermal imager (16) to locate the heat source of gas leakage. The video data acquisition module (12) captures images of the pool surface, identifies the distribution of garbage and foam, and synchronizes the data to the monitoring backend (5) for anomaly analysis; S5. Inspection of the deep processing unit: The drone enters the deep processing unit, and the three-dimensional scanning module (10) and the video data acquisition module (12) work together to monitor the running trajectory of the sludge scraper in the secondary sedimentation tank and the height of the mud layer on the surface of the tank. The image recognition module analyzes the clarity of the effluent from the high-efficiency sedimentation tank by measuring the light transmittance of the water body and detects the cleanliness of the inclined tube; The thermal imager (16) scans the valves and pipes of the denitrification filter to identify hot spots of leakage; The video data acquisition module (12) captures the screen parameters of the membrane tank blower, and the vibration monitoring module analyzes the operating stability of the blower; S6. Data transmission and automatic charging: During the inspection, the UAV body (1) transmits data to the monitoring backend (5) in real time through the communication interface module (3), and the charging station (4) receives status information synchronously. When the battery level is lower than the preset threshold, the autonomous charging module (8) triggers the return command, the drone docking cabin (18) opens automatically, and the drone enters and starts wireless charging. The charging station (4) synchronizes the full amount of data collected by the drone with the monitoring backend (5) via optical fiber, including the three-dimensional scanning model, images and detection parameters; S7. Abnormal alarm and data archiving: The intelligent alarm module (9) performs real-time analysis of the collected data. When it detects abnormalities such as battery abnormality, equipment failure due to camera obstruction, collision or impassable path obstacle, environmental parameters exceeding the standard or personnel intrusion, or intelligent identification abnormality of pipe cracks, it automatically sends an alarm signal to the monitoring background (5). The data comparison module compares real-time data with historical benchmark values ​​to generate equipment status trend reports. The defect detection results of the image recognition module are fused with 3D scanning data to form a visualized inspection file. The monitoring backend (5) triggers the corresponding handling process according to the alarm level, and archives and stores the complete inspection data for subsequent analysis and optimization.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the unmanned aerial vehicle-based underground sewage treatment plant inspection method as described in claim 8.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the unmanned aerial vehicle-based underground sewage treatment plant inspection method as described in claim 8.

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