A Smart Detection and Emergency Response System for Thin Oil Films Based on Multi-Source Information Fusion

Abstract

This invention discloses an intelligent oil spill detection and emergency response system based on multi-source information fusion, comprising: multiple intelligent surface oil spill detection and recovery devices and a remote monitoring and cluster scheduling platform; the intelligent surface oil spill detection and recovery devices include: an autonomous navigation vehicle serving as a mobile platform and support structure on the water; a collaborative sensing module for acquiring multi-source heterogeneous information about the surface environment; a dynamic path planning and decision-making unit for generating and optimizing recovery operation paths in real time based on multi-source heterogeneous environmental information, and controlling the navigation of the autonomous navigation vehicle and oil spill recovery operations; a high-efficiency oil-water separation and collection module for adsorbing, separating, and storing recovered oil; and a remote monitoring and cluster scheduling platform connected to multiple intelligent surface oil spill detection and recovery devices to achieve task assignment, status monitoring, and multi-machine collaborative scheduling. This provides an efficient and flexible technical equipment solution for marine environmental protection.

Description

Technical Field

[0001] This invention relates to the field of marine environmental monitoring and emergency response technology, specifically to an intelligent detection and emergency response system for thin oil films based on multi-source information fusion. Background Technology

[0002] Oil spills at sea pose a persistent threat to marine ecology and the economy. Current oil spill response technologies typically separate the "detection," "decision-making," and "recovery" processes: satellite or aerial remote sensing handles large-scale detection, but lacks real-time performance and resolution; recovery equipment (such as oil booms and skimmers) relies on manual deployment and operation, resulting in slow response times and low efficiency in handling thin oil films and dynamically spreading oil fields. In recent years, while some research has attempted to integrate sensors into unmanned vessels, these methods generally suffer from problems such as single perception modalities, rigid algorithms, and static, inflexible path planning. They are unable to adapt to the dynamic changes in the form, location, and extent of oil spills in real-world marine environments, and even more difficult to achieve collaborative intelligent operations involving multiple pieces of equipment. Therefore, there is an urgent need for an integrated system capable of accurately sensing oil fields in real time, autonomously and intelligently planning paths, and efficiently executing recovery tasks. Summary of the Invention

[0003] To address the problems of isolated oil spill detection methods, unintelligent recovery path planning, and poor system adaptability in existing technologies, the technical solution adopted in this invention is: a thin oil film intelligent detection and emergency response system based on multi-source information fusion, comprising: multiple intelligent water surface oil spill detection and recovery devices and a remote monitoring and cluster scheduling platform; The intelligent oil spill detection and recovery device includes: Autonomous navigation vehicle: used as a mobile platform and load-bearing structure on water; Collaborative sensing module: installed on the autonomous navigation vehicle, used to acquire multi-source heterogeneous information about the water surface environment, including oil spill characteristic information, obstacle information and hydro-meteorological information; Dynamic path planning and decision-making unit: Based on the multi-source heterogeneous environmental information output by the collaborative sensing module, it generates and optimizes the recovery operation path in real time, and controls the navigation of the autonomous vehicle and the oil spill recovery operation. High-efficiency oil-water separation and collection module: installed on the autonomous navigation vehicle, used to adsorb and separate oil spills on the water surface and store the recovered oil; The remote monitoring and cluster scheduling platform is connected to multiple intelligent oil spill detection and recovery devices via a wireless communication network to achieve task assignment, status monitoring and multi-machine collaborative scheduling.

[0004] Furthermore, the collaborative sensing module includes: The hyperspectral imaging unit is used to acquire continuous spectral information of the water surface and identify the type of oil film and the area range of the oil spill through spectral demixing and feature extraction. The infrared thermal imaging unit utilizes the temperature difference between the oil film and the water surface to assist in detecting the thickness of the oil film; Synthetic aperture radar unit, used for all-weather detection of radar backscattering coefficient changes caused by oil film on water surface; A multi-parameter water quality sensor that monitors water pH, dissolved oxygen, and oil concentration gradients in real time. The environmental sensing unit is used to acquire dynamic information about the on-site working environment.

[0005] Furthermore, the dynamic path planning and decision-making unit runs an adaptive offshore oilfield cover path planning algorithm, which uses a real-time oil slick probability distribution map. Current location of the carrier Environmental dynamics As input, an online decision is made through a reinforcement learning model based on a Deep Q-Network (DQN), which outputs the optimal heading and velocity for the next time step. Reward function of a reinforcement learning model improved based on Deep Q-Network (DQN) Designed as follows:

[0006] in, The expected increase in coverage area due to the decision-making process. This is a path duplication rate penalty term. To combat environmental disturbances Furthermore, the high-efficiency oil-water separation and collection module adopts a modular negative pressure adsorption and centrifugation synergistic working mode, including: The deployable negative pressure suction head array dynamically adjusts the number of openings and suction power according to the oil film distribution density to achieve selective and efficient adsorption; The primary cyclone separator performs the first coarse separation of oil-water mixture drawn in by the deployable negative pressure suction head array using air flotation and cyclone centrifugation. The fine separation membrane module receives the oil-water emulsion after primary separation from the primary cyclone separator and performs deep separation using a superoleophilic and hydrophobic filter membrane to produce oil with low water content. An integrated oil storage tank is used to store the separated oil delivered by the fine separation membrane assembly.

[0007] Furthermore, the integrated oil reservoir also includes an online monitoring sensor for liquid level and oil purity installed inside.

[0008] Furthermore, the remote monitoring and cluster scheduling platform is connected to multiple intelligent oil spill detection and recovery devices via a wireless communication network, and the process of task assignment, status monitoring, and multi-machine collaborative scheduling is as follows: Receive real-time status, sensing data, and planned paths from one or more intelligent oil spill detection and recovery devices; Based on a global oil spill prediction model, task areas are dynamically allocated to the intelligent surface oil spill detection and recovery devices in the cluster. In the event of a communication interruption, a pre-defined emergency behavior strategy based on Bayesian inference is implemented to ensure the autonomous security of the carrier. A method for intelligent oil spill recovery on water surface based on a multi-source information fusion-based intelligent detection and emergency response system for thin oil films, comprising the following steps: S1: Mission initialization, the autonomous vehicle receives target area information or autonomously enters the preset patrol area; S2: The collaborative sensing module starts to synchronously collect and preprocess multi-source data; S3: The dynamic path planning and decision-making unit generates a real-time optimized operation path based on the fused oil film detection results and environmental information, and controls the carrier's navigation. S4: When the detection device detects that the oil film thickness exceeds the preset threshold and the oil film concentration reaches the recyclable standard, it determines that it has entered the effective recycling area. When it determines that it has entered the effective recycling area, it automatically starts the high-efficiency oil-water separation and collection module and adaptively adjusts the adsorption intensity according to the oil film density. S5: During operation, it continuously transmits key data back to the remote monitoring and cluster scheduling platform and receives scheduling instructions; S6: When the oil storage capacity is saturated, the oil film is cleared, or a return command is received, plan the optimal route back to base.

[0009] Furthermore, in the cluster operation mode, multiple carriers communicate through the scheduling platform or local self-organizing network, and adopt a "leader-follower" or "distributed auction" mechanism to dynamically divide the operation sub-areas, so as to achieve efficient collaborative coverage and recovery of large-scale irregular oil spill sites.

[0010] This invention provides an intelligent detection and emergency response system for thin oil slicks based on multi-source information fusion. It mainly includes an autonomous navigation vehicle, a collaborative sensing module, a dynamic path planning and decision-making unit, an efficient oil-water separation and collection module, and a remote monitoring and cluster scheduling platform. Through innovative multi-source information fusion sensing, reinforcement learning-based dynamic path planning, and modular adaptive recovery design, a highly intelligent, adaptable, and cluster-operable oil spill detection and recovery system for water surfaces is constructed, providing an efficient and flexible technical equipment solution for marine environmental protection. 1. Collaborative Sensing Module: Employs multi-source data acquisition using hyperspectral imaging (oil type identification), infrared thermal imaging (nighttime / auxiliary detection), synthetic aperture radar (all-weather, wide-area), water quality sensors (edge-assisted), and environmental sensors. Through a deep neural network model that fuses feature-level and decision-level data, it outputs an oil film distribution probability map and thickness estimation map with confidence levels.

[0011] 2. Dynamic Path Planning and Decision-Making Unit: This is one of the core innovations of the system. The unit receives real-time oil film probability maps, carrier state data, and environmental dynamic field data. An improved reinforcement learning framework is used for online path planning. Its state space includes the oil film entropy, historical coverage, and environmental vectors of the area surrounding the carrier; the action space is a discrete combination of heading and velocity; and the reward function comprehensively considers coverage gain, path efficiency, and energy consumption. This algorithm enables the carrier to actively track high-density oil film areas like an "intelligent cleaner" and adapt to the drift and diffusion of oil film with wind and current.

[0012] 3. High-efficiency oil-water separation and collection module: Adopting a modular design. The front end is a negative pressure suction head array that can be deployed / retracted according to instructions to achieve "on-demand adsorption". The oil-water mixture passes through a primary cyclone separator (removing most of the water and crude oil) and a fine separation membrane module (deep dehydration), and finally the high-purity oil is stored in a flexible oil storage tank.

[0013] 4. Remote Monitoring and Cluster Scheduling Platform: Constructs a system-level digital twin to achieve virtual-real interaction. The platform can allocate tasks, divide areas, and resolve conflicts among multiple carriers, forming a collaborative "swarm" for data recovery.

[0014] Beneficial effects: 1. Strong sensing capability and anti-interference: Multi-source heterogeneous information fusion overcomes the limitations of a single sensor, improving the accuracy, robustness and all-weather working capability of oil film detection.

[0015] 2. Intelligent and dynamic path planning: Based on reinforcement learning, the planning algorithm enables the recovery path to respond in real time to changes in the oilfield and environmental disturbances, thereby maximizing coverage efficiency.

[0016] 3. Adaptive recovery operation: The modular adsorption and separation design can adjust the working mode according to the oil film condition, improving recovery efficiency and energy utilization.

[0017] 4. Good system coordination: It supports multi-machine cluster operation and achieves efficient coordination through central scheduling or distributed algorithms to deal with large-scale oil spill accidents.

[0018] 5. High efficiency in both peacetime and wartime use: It can be used for routine inspection and monitoring of oil spills in water areas, and can be quickly converted into a highly efficient recovery force in the event of an accident. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is an overall structural view of a thin oil film intelligent detection and emergency response system based on multi-source information fusion; Figure 2 This is a schematic diagram illustrating the working principle of the biomimetic adsorption oil collection system of the present invention; Figure 3 This is a schematic flowchart of the oil-water cyclone separation and oil storage system of the present invention; Figure 4 This is a software architecture and workflow diagram of the central control and decision-making system of the present invention; Figure 5 This is a schematic diagram of a reinforcement learning model improved based on Deep Q-Network (DQN). Figure 6 This is a schematic diagram based on a global oil spill prediction model. Detailed Implementation

[0021] It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0022] 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 following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Figure 1 This is an overall structural view of the intelligent detection and emergency response system for thin oil films based on multi-source information fusion, as described in this invention. A thin oil film intelligent detection and emergency response system based on multi-source information fusion includes: multiple intelligent oil spill detection and recovery devices and a remote monitoring and cluster scheduling platform; The intelligent oil spill detection and recovery device includes: Autonomous navigation vehicle: used as a mobile platform and load-bearing structure on water; Collaborative sensing module: installed on the autonomous navigation vehicle, used to acquire multi-source heterogeneous information about the water surface environment, including oil spill characteristic information, obstacle information and hydro-meteorological information; Dynamic path planning and decision-making unit: Based on the multi-source heterogeneous environmental information output by the collaborative sensing module, it generates and optimizes the recovery operation path in real time, and controls the navigation of the autonomous vehicle and the oil spill recovery operation. High-efficiency oil-water separation and collection module: installed on the autonomous navigation vehicle, used to adsorb and separate oil spills on the water surface and store the recovered oil; The remote monitoring and cluster scheduling platform is connected to multiple intelligent oil spill detection and recovery devices via a wireless communication network to achieve task assignment, status monitoring and multi-machine collaborative scheduling.

[0024] Furthermore, the collaborative sensing module includes: The hyperspectral imaging unit is used to acquire continuous spectral information of the water surface and identify the type of oil film and the area range of the oil spill through spectral demixing and feature extraction. The infrared thermal imaging unit utilizes the temperature difference between the oil film and the water surface to assist in detecting the thickness of the oil film, especially at night or under low light conditions. Synthetic aperture radar unit, used for wide-area, all-weather detection of radar backscattering coefficient changes caused by oil film on water surface; A multi-parameter water quality sensor monitors water pH, dissolved oxygen, and oil concentration gradients in real time, providing auxiliary information for oil film edge detection. The environmental sensing unit is used to acquire dynamic information about the on-site working environment.

[0025] The environmental sensing unit includes: an anemometer, a current meter, and a binocular vision obstacle avoidance camera. Furthermore, the dynamic path planning and decision-making unit runs an adaptive offshore oilfield cover path planning algorithm, which uses a real-time oil slick probability distribution map. Current location of the carrier Environmental dynamics As input, an online decision is made through a reinforcement learning model based on a deep Q-network (DQN), which outputs the optimal heading and velocity for the next time step. Reward function of a reinforcement learning model improved based on Deep Q-Network (DQN) Designed as follows:

[0026] in, The expected increase in coverage area due to the decision-making process. This is a path duplication rate penalty term. To counteract the energy consumption penalty for environmental disturbances, These are the weighting coefficients.

[0027] An improved reinforcement learning model based on Deep Q-Network (DQN) is as follows: Figure 2 As shown; Figure 3 It is the software architecture and workflow diagram of the dynamic path planning and decision-making unit; The dynamic path planning and decision-making unit includes: Oil spill detection module: used to detect oil spills on the sponge; Fusion module: Fuses multispectral and laser fluorescence data, performs real-time image analysis to identify oil slick pixel regions, and generates an electronic nautical chart of oil spill distribution; Precision recognition module: Uses millimeter-wave radar point cloud data and optical data to identify and track obstacles; Autonomous decision-making and route planning module; pre-approves route patrol based on patrol mode, switches to recovery operation mode in emergency situations, and calculates the route to the maximum area of ​​oilfield coverage.

[0028] Figure 4 This is a schematic diagram illustrating the working principle of the high-efficiency oil-water separation and collection module of the present invention; Figure 5 This is a schematic flowchart of the oil-water cyclone separation and oil storage system of the present invention; Furthermore, the high-efficiency oil-water separation and collection module adopts a modular negative pressure adsorption and centrifugation synergistic working mode, including: The deployable negative pressure suction head array dynamically adjusts the number of openings and suction power according to the oil film distribution density to achieve selective and efficient adsorption; The primary cyclone separator performs the first coarse separation of oil-water mixture drawn in by the deployable negative pressure suction head array using air flotation and cyclone centrifugation. The fine separation membrane module receives the oil-water emulsion after primary separation from the primary cyclone separator and performs deep separation using a superoleophilic and hydrophobic filter membrane to produce oil with low water content. An integrated oil storage tank is used to store the separated oil delivered by the fine separation membrane assembly.

[0029] It also includes an online monitoring sensor for liquid level and oil purity installed inside the integrated oil storage tank.

[0030] Furthermore, the remote monitoring and cluster scheduling platform is connected to multiple intelligent oil spill detection and recovery devices via a wireless communication network, and the process of task assignment, status monitoring, and multi-machine collaborative scheduling is as follows: Receive real-time status, sensing data, and planned paths from one or more intelligent oil spill detection and recovery devices; Based on a global oil spill prediction model, task areas are dynamically allocated to the intelligent surface oil spill detection and recovery devices in the cluster. In the event of a communication interruption, a pre-set emergency behavior strategy based on Bayesian inference is implemented to ensure the autonomous and safe operation of the carrier.

[0031] The global oil spill prediction model, as follows Figure 6 As shown; A smart oil spill recovery method based on any one of the systems described above includes the following steps: S1: Mission initialization, the autonomous vehicle receives target area information or autonomously enters the preset patrol area; S2: The collaborative sensing module starts to synchronously collect and preprocess multi-source data; S3: The dynamic path planning and decision-making unit generates a real-time optimized operation path based on the fused oil film detection results and environmental information, and controls the carrier's navigation. S4: When it is determined that the effective recovery area has been entered, the high-efficiency oil-water separation and collection module is automatically started, and the adsorption intensity is adaptively adjusted according to the oil film density. S5: During operation, it continuously transmits key data (oil film characteristics, environmental characteristics, equipment status) back to the remote monitoring and cluster scheduling platform and receives scheduling instructions; S6: When the oil storage capacity is saturated, the oil film is cleared, or a return command is received, plan the optimal route back to base.

[0032] Furthermore, in the cluster operation mode, multiple carriers communicate through the scheduling platform or local self-organizing network, and adopt a "leader-follower" or "distributed auction" mechanism to dynamically divide the operation sub-areas, so as to achieve efficient collaborative coverage and recovery of large-scale irregular oil spill sites.

[0033] Example 1 A single unmanned surface vessel, 4 meters long and 1.8 meters wide, serves as the autonomous navigation platform. In the collaborative perception module, a hyperspectral camera and an infrared thermal imager are mounted on a rotating gimbal, a miniaturized synthetic aperture radar is mounted on one side of the hull, and a water quality sensor is placed at the bow where the vessel enters the water.

[0034] Work process: The system is deployed in nearshore areas. During one inspection, the infrared unit of the collaborative sensing module first detected an area of ​​abnormal temperature, which was then confirmed by hyperspectral and radar. The fusion algorithm determined it to be a medium-thickness crude oil film, covering an area of ​​approximately 500 square meters, and generated an initial probability distribution map.

[0035] Based on this map and the current southeast wind (level 2), the dynamic path planning unit calculates the first tracking path using a built-in reinforcement learning model. The unmanned surface vessel (USV) navigates along this path and activates two negative pressure suction heads located in the middle of the vessel. During the recovery process, the oil film spreads westward due to the wind. The perception module continuously updates the oil film map, and the path planning unit recalculates every 5 seconds, guiding the USV to adaptively adjust its course, always staying at the forefront of the highest oil film concentration. After two-stage separation, the adsorbed oil-water mixture is stored in a 600-liter oil storage bladder. Simultaneously, the remote monitoring center observes the operation and oil film recession in real time via a 5G link. When it is determined that the single vessel's cleaning speed is insufficient, the center dispatches another nearby USV of the same type to provide support. The two vessels are allocated through the platform and work collaboratively in a "parallel operation" manner, significantly reducing the cleaning time.

[0036] When the oil level in the reservoir reaches 85% or the oil film probability map shows a cleanup completion rate of over 95%, the unmanned vessel automatically plans its return route, returns to the dock to drain the oil and recharge, and prepares to carry out the next mission.

[0037] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A thin oil film intelligent detection and emergency response system based on multi-source information fusion, characterized in that, include: Multiple intelligent oil spill detection and recovery devices and a remote monitoring and cluster dispatch platform; The intelligent oil spill detection and recovery device includes: Autonomous navigation vehicle: used as a mobile platform and load-bearing structure on water; Collaborative sensing module: installed on the autonomous navigation vehicle, used to acquire multi-source heterogeneous information about the water surface environment, including oil spill characteristic information, obstacle information and hydro-meteorological information; Dynamic path planning and decision-making unit: Based on the multi-source heterogeneous environmental information output by the collaborative sensing module, it generates and optimizes the recovery operation path in real time, and controls the navigation of the autonomous vehicle and the oil spill recovery operation. High-efficiency oil-water separation and collection module: installed on the autonomous navigation vehicle, used to adsorb and separate oil spills on the water surface and store the recovered oil; The remote monitoring and cluster scheduling platform is connected to multiple intelligent oil spill detection and recovery devices via a wireless communication network to achieve task assignment, status monitoring and multi-machine collaborative scheduling.

2. The intelligent detection and emergency response system for thin oil films based on multi-source information fusion according to claim 1, characterized in that, The collaborative sensing module includes: The hyperspectral imaging unit is used to acquire continuous spectral information of the water surface and identify the type of oil film and the area range of the oil spill through spectral demixing and feature extraction. The infrared thermal imaging unit utilizes the temperature difference between the oil film and the water surface to assist in detecting the thickness of the oil film; Synthetic aperture radar unit, used for all-weather detection of radar backscattering coefficient changes caused by oil film on water surface; A multi-parameter water quality sensor that monitors water pH, dissolved oxygen, and oil concentration gradients in real time. The environmental sensing unit is used to acquire dynamic information about the on-site working environment.

3. The intelligent detection and emergency response system for thin oil films based on multi-source information fusion according to claim 1, characterized in that, The dynamic path planning and decision-making unit runs an adaptive marine oilfield cover path planning algorithm, which uses a real-time oil film probability distribution map. Current location of the carrier Environmental dynamics As input, an online decision is made through a reinforcement learning model based on a Deep Q-Network (DQN), which outputs the optimal heading and velocity for the next time step. Reward function of a reinforcement learning model improved based on Deep Q-Network (DQN) Designed as follows: in, The expected increase in coverage area due to the decision-making process. This is a path duplication rate penalty term. To combat environmental disturbances.

4. The intelligent detection and emergency response system for thin oil films based on multi-source information fusion according to claim 1, characterized in that, The high-efficiency oil-water separation and collection module adopts a modular negative pressure adsorption and centrifugation combined working mode, including: The deployable negative pressure suction head array dynamically adjusts the number of openings and suction power according to the oil film distribution density to achieve selective and efficient adsorption; The primary cyclone separator performs the first coarse separation of oil-water mixture drawn in by the deployable negative pressure suction head array using air flotation and cyclone centrifugation. The fine separation membrane module receives the oil-water emulsion after primary separation from the primary cyclone separator and performs deep separation using a superoleophilic and hydrophobic filter membrane to produce oil with low water content. An integrated oil storage tank is used to store the separated oil delivered by the fine separation membrane assembly.

5. The intelligent detection and emergency response system for thin oil films based on multi-source information fusion according to claim 4, characterized in that, It also includes an online monitoring sensor for liquid level and oil purity installed inside the integrated oil storage tank.

6. The intelligent detection and emergency response system for thin oil films based on multi-source information fusion according to claim 4, characterized in that, The remote monitoring and cluster scheduling platform is connected to multiple intelligent oil spill detection and recovery devices via a wireless communication network, and the process of task assignment, status monitoring and multi-machine collaborative scheduling is as follows: Receive real-time status, sensing data, and planned paths from one or more intelligent oil spill detection and recovery devices; Based on a global oil spill prediction model, task areas are dynamically allocated to the intelligent surface oil spill detection and recovery devices in the cluster. In the event of a communication interruption, a pre-defined emergency behavior strategy based on Bayesian inference is implemented to ensure the autonomous security of the carrier.

7. A method for intelligent oil spill recovery on water surface based on a multi-source information fusion-based intelligent detection and emergency response system for thin oil films as described in any one of claims 1-6, characterized in that, Includes the following steps: S1: Mission initialization, the autonomous vehicle receives target area information or autonomously enters the preset patrol area; S2: The collaborative sensing module starts to synchronously collect and preprocess multi-source data; S3: The dynamic path planning and decision-making unit generates a real-time optimized operation path based on the fused oil film detection results and environmental information, and controls the carrier's navigation. S4: When the detection device detects that the oil film thickness exceeds the preset threshold and the oil film concentration reaches the recyclable standard, it determines that it has entered the effective recycling area. When it determines that it has entered the effective recycling area, it automatically starts the high-efficiency oil-water separation and collection module and adaptively adjusts the adsorption intensity according to the oil film density. S5: During operation, it continuously transmits key data back to the remote monitoring and cluster scheduling platform and receives scheduling instructions; S6: When the oil storage capacity is saturated, the oil film is cleared, or a return command is received, plan the optimal route back to base.

8. The method according to claim 7, characterized in that, In cluster operation mode, multiple carriers communicate through the scheduling platform or local self-organizing network, and adopt a "leader-follower" or "distributed auction" mechanism to dynamically divide the operation sub-areas, so as to achieve efficient collaborative coverage and recovery of large-scale irregular oil spill sites.

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