Offshore wind field anti-collision and floating object treatment system and operation method

Abstract

The invention discloses an anti-collision and floating object treatment system and method for an offshore wind field. The system comprises an annular protection belt, a spherical anti-collision unit, a monitoring network, cleaning equipment and a control center. The annular protection belt is formed by a spherical anti-collision device array arranged along the red line of a wind field, each spherical anti-collision unit comprises an anchor chain suction barrel, a spherical body and a rotating mechanism, and a damping buffer layer is arranged on the inner wall of each spherical anti-collision unit. The monitoring network integrates the infrared touch induction network and the SAR radar to realize full-range monitoring; the control center dispatches the unmanned aerial vehicle, the unmanned ship and the interception net to process the floating objects in a hierarchical manner through a decision tree algorithm, and dynamically predicts the service life of equipment in combination with an intelligent maintenance module. The anti-collision effect and the monitoring efficiency are improved, the labor cost is reduced, and the method is suitable for offshore wind field safety protection.

Description

Technical Field

[0001] This invention relates to the field of offshore wind power facility protection technology, specifically to an offshore wind farm collision avoidance and floating object handling system and its operation method. Background Technology

[0002] With the rapid development of the global offshore wind power industry, the safe operation of offshore wind farms faces many challenges, among which the issues of floating object impacts and the maintenance of protective facilities are particularly prominent.

[0003] Traditional offshore wind farms generally suffer from the following technical deficiencies: 1. The wind farm lacks dedicated protective facilities, leaving wind turbine foundations such as monopiles and jackets directly exposed to impact risks. Floating debris such as ship wreckage, buoys, fishing nets, and seabed debris such as pile fragments can easily enter the wind farm with ocean currents. Impacts from these objects can damage the foundation structure, destroy the anti-corrosion layer, and even cause equipment shutdowns, resulting in significant economic losses. 2. Existing monitoring methods rely on manual inspections or low-precision radar, which cannot identify the location, size, and trajectory of floating objects in real time and accurately. Manual inspections are greatly affected by sea conditions and weather, and cannot be carried out when the wave height is greater than 2 meters. Moreover, the efficiency is extremely low at night. Traditional radar has a resolution of more than 5 meters, which makes it difficult to detect small and medium-sized floating objects, i.e., floating objects with a diameter of less than 2 meters, resulting in delayed warnings and missing the best time for handling. 3. Floating debris removal mainly relies on manual boat salvage, which is costly and inefficient. There is a lack of efficient interception methods for large floating objects, making it easy for them to slip through. At the same time, although some wind farms have simple protective structures, they are mostly fixed and lack adaptability. After long-term use, they are easily damaged by seawater corrosion and repeated impacts. Moreover, the maintenance cycle is fixed at 5 years and cannot be dynamically adjusted according to the actual condition, resulting in prominent problems of over-maintenance or delayed maintenance. 4. The existing system lacks a graded treatment mechanism for floating objects of different types and sizes. Regardless of the size of the floating object, the same treatment method is used, which leads to waste of resources or insufficient treatment capacity, further increasing the risk of wind farm operation. Summary of the Invention

[0004] In response to the problems mentioned in existing technologies, there is an urgent need to build a comprehensive system that integrates passive protection, active monitoring, intelligent processing, and dynamic maintenance to solve the above-mentioned technical pain points and ensure the safe and stable operation of offshore wind farms.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A collision avoidance and floating object handling system for offshore wind farms, comprising a ring-shaped protective belt, spherical collision avoidance units, a monitoring network, cleaning equipment, and a control center; The annular protective belt includes an array of spherical anti-collision devices arranged at intervals along the wind farm red line; The spherical anti-collision unit consists of an anchor chain suction cylinder and a spherical body installed on top of it. The inner wall of the spherical body is provided with a damping buffer layer, and a rotating mechanism driven by a variable frequency motor is configured inside. The rotating mechanism is connected to a wind turbine generator through a power supply line, and the rotation speed is dynamically adjusted with the wind speed. The monitoring network includes an infrared touch sensing network and an AR radar module; wherein the infrared touch sensing network is composed of multiple layers of horizontal infrared sensing lines connecting adjacent spherical devices, and the SAR radar module is used to scan the sea area surrounding the wind field to identify the position, size, speed and trajectory of floating objects. The cleaning equipment includes unmanned boats, drones, and electrically raised interception nets, wherein the unmanned boats and drones are each equipped with grabbing devices, and the bottom of the electrically raised interception nets is fixed by anchor chains. The control center communicates with the ring-shaped protective belt, spherical anti-collision units, monitoring network, and cleaning equipment. It is configured with a decision tree algorithm to classify risk levels as yellow, orange, and red. A yellow alert is issued for floating objects with a diameter of no more than 2 meters and a speed of no more than 1 meter per second, and drones will be dispatched to handle them. An orange alert is issued for floating objects with a diameter greater than 2 meters and a speed of no more than 1 meter per second. An interception net is activated and unmanned boats are dispatched. A red alert is issued for floating objects with a diameter greater than 2 meters and a speed greater than 1 meter per second, simultaneously triggering an interception net, unmanned vessel, and emergency alarm.

[0006] In the preferred embodiment, the spherical body is made of elastic alloy steel with a diameter adapted to the wind field protection requirements, and the spherical structure can disperse the impact force through the curved surface; the anchor chain suction cylinder is vertically inserted into the seabed soil layer and achieves a stable connection with the seabed through the suction effect, and its cylinder size is designed according to the weight of the spherical body and the geological conditions of the sea area. The damping buffer layer is made of highly elastic damping material and covers the inner wall of the spherical body. It absorbs and dissipates impact energy through material deformation, thereby reducing the impact force transmitted to the anchor chain suction cylinder. The rotation speed adjustment logic of the rotating mechanism is as follows: when the wind speed is low, the rotation speed is maintained at a low speed to reduce energy consumption; when the wind speed increases, the rotation speed increases with the increase of wind turbine power generation; the centrifugal force generated by the rotation helps to push away small floating objects and reduce their continuous contact time with the spherical body.

[0007] In a preferred embodiment, the multi-layered horizontal infrared sensing lines of the infrared touch sensing network are distributed at intervals along the vertical direction to form a three-dimensional sensing area, which can identify floating objects at different heights. After triggering, it can quickly locate the touch position and transmit precise coordinates to the control center. The scanning range of the SAR radar module covers a certain distance of sea area around the wind field, and continuously monitors at a fixed period, which can identify floating objects within a certain diameter range and track their movement trajectory. In a preferred embodiment, the unmanned surface vessel is equipped with a grasping device that can adapt to different types of floating objects and has grasping, cutting, or towing functions; the unmanned aerial vehicle's grasping device has a lightweight structure and is suitable for quickly grasping small floating objects; both maintain real-time data interaction with the control center via wireless communication to provide feedback on the task execution status; the electrically operated lifting interception net can adjust its height according to instructions, rising to near the water surface to form a physical barrier during interception, and lowering underwater to reduce water flow resistance when not in operation.

[0008] In the preferred embodiment, the decision tree algorithm of the control center uses the diameter and speed of the floating object as core parameters, and combines them with the predicted trajectory of the object to determine the risk level. Different levels correspond to preset equipment linkage strategies to ensure timely and targeted responses. In a preferred embodiment, the system further includes an intelligent maintenance module. This module collects real-time equipment operating status data, including structural stress, corrosion level, and circuit continuity, through sensors deployed on the spherical anti-collision device and monitoring network. By analyzing the data, it determines whether the equipment has a fault and the type of fault. For minor faults, it automatically dispatches unmanned equipment to replace components, and for serious faults, it generates a manual maintenance work order containing the fault location and preliminary repair plan.

[0009] A method for operating a collision avoidance and floating object handling system for offshore wind farms includes the following steps: The S1 and SAR radar modules scan the surrounding sea area at fixed intervals to identify floating objects and record their location, size, speed and trajectory. S2. When a floating object enters a certain range of the wind field red line and touches the infrared touch sensor network, the local alarm device is triggered, and at the same time, a signal containing detailed parameters of the floating object is sent to the control center within a short period of time. S3. After receiving the signal, the control center uses a decision tree algorithm to classify the risk level of the floating objects and activates the preset response strategy according to the corresponding level, and dispatches the corresponding equipment to perform the cleanup task. S4, the intelligent maintenance module continuously monitors the status of system equipment, diagnoses faults and schedules maintenance resources based on monitoring data, and dynamically predicts equipment maintenance cycles based on historical data and environmental parameters.

[0010] In the preferred embodiment, in step S1, if the SAR radar module detects a floating object but it does not enter the near field range, it will continuously track its trajectory and update the data until the floating object leaves the monitoring range or enters the near field area; the local alarm device in step S2 is a device that can emit an alarm sound.

[0011] In the preferred embodiment, in step S3, after receiving the dispatch instruction, the UAV navigates to the location of the target floating object, uses its own grasping device to grasp it, and transports it to the designated collection point; when handling large floating objects, the unmanned vessel can choose to use grasping, cutting, or towing methods according to the type of floating object to transfer it to the designated area.

[0012] In the preferred embodiment, in step S4, the intelligent maintenance module, when predicting the maintenance cycle, comprehensively considers the equipment operating time, marine environmental factors, and historical fault patterns to generate a dynamic maintenance plan. At the same time, the unmanned vessel simultaneously inspects the surrounding equipment while performing the cleaning task, thereby improving maintenance efficiency.

[0013] A collision avoidance and floating debris handling system and operation method for offshore wind farms, the beneficial effects of which include, but are not limited to, the following: 1. This invention forms a reliable physical barrier through the coordinated design of a ring-shaped protective belt and a spherical anti-collision unit. The spherical body is made of elastic alloy steel, combined with an inner wall damping buffer layer, which can disperse the impact force and absorb most of the impact energy through the curved surface, significantly reducing the risk of structural damage to the wind turbine foundation caused by floating objects. The rotating mechanism dynamically adjusts its speed according to the wind speed, using centrifugal force to help push away small floating objects, reducing the probability of continuous impact and effectively reducing unplanned downtime. 2. The monitoring network integrates SAR radar long-range scanning with infrared touch-sensing network short-range triggering technology to achieve full-range, high-precision monitoring of the wind field's perimeter. SAR radar can identify small floating objects, and combined with the rapid response of the infrared sensing network, it solves the problems of slow identification of small and medium-sized floating objects and low efficiency at night and in severe weather conditions associated with traditional monitoring methods. Through data fusion and dynamic trajectory tracking, the early warning response speed is significantly improved, ensuring timely detection of floating object intrusion risks. 3. A risk grading mechanism based on decision tree algorithms is used to match differentiated processing strategies for floating objects of different sizes and speeds: small floating objects are quickly captured by drones, while large floating objects are pre-intercepted by interception nets and processed by unmanned vessels, achieving full automation of the process. Compared with traditional manual salvage, the efficiency of floating object handling is significantly improved, and it is not limited by sea conditions, can operate stably in complex environments, and reduces processing costs; 4. The intelligent maintenance module collects equipment status data in real time through sensors and dynamically predicts maintenance cycles by combining machine learning models with environmental parameters, replacing traditional fixed cycles and avoiding over-maintenance or delayed maintenance. The unmanned vessel simultaneously performs equipment inspections during cleaning tasks. For minor faults, it automatically schedules unmanned equipment to replace parts; for major faults, it generates precise repair plans, reducing facility failure rates, extending equipment lifespan, and further reducing operating costs. Attached Figure Description

[0014] Figure 1Schematic diagram of an offshore wind farm collision avoidance and floating debris handling system; Figure 2 A step-by-step diagram illustrating the operation of an offshore wind farm collision avoidance and floating debris handling system. Detailed Implementation

[0015] like Figure 1 As shown, a marine wind farm collision avoidance and floating object handling system includes a ring-shaped protective belt, a spherical collision avoidance unit, a monitoring network, cleaning equipment, and a control center. The ring-shaped protective belt includes an array of spherical anti-collision devices arranged at intervals along the wind field red line. The spacing between adjacent devices is set according to the distribution density of floating objects around the wind field and the characteristics of ocean currents, forming a continuous ring-shaped physical barrier that can block or buffer floating objects approaching the wind field from all directions. The spherical anti-collision unit consists of an anchor chain suction cylinder and a spherical body installed on top of it. The inner wall of the spherical body is provided with a damping buffer layer, and a rotating mechanism driven by a variable frequency motor is configured inside. The rotating mechanism is connected to a wind turbine generator through a power supply line. The rotation speed is dynamically adjusted with the wind speed. When the wind speed is low, it maintains a low speed operation, and when the wind speed increases, the rotation speed is increased synchronously to enhance the protective effect. The monitoring network includes an infrared motion sensing network and a SAR radar module. The infrared motion sensing network consists of multiple layers of horizontal infrared sensing lines connecting adjacent spherical devices. Each layer of sensing lines is distributed vertically to cover different height ranges. The SAR radar module is used to scan the sea area surrounding the wind field, continuously identifying the position, size, speed, and trajectory of floating objects, forming long-distance monitoring data. The cleaning equipment includes unmanned surface vessels (USVs), unmanned aerial vehicles (UAVs), and an electrically operated lifting interception net. The USVs and UAVs are equipped with grabbing devices. The grabbing devices of the USVs are suitable for large or heavy floating objects, while the grabbing devices of the UAVs are suitable for light and small floating objects. The bottom of the electrically operated lifting interception net is fixed to the seabed by anchor chains and its height can be adjusted according to commands to adapt to different interception needs. The control center communicates with the ring-shaped protective belt, spherical anti-collision units, monitoring network, and cleaning equipment. It is configured with a decision tree algorithm to classify risk levels as yellow, orange, and red. A yellow alert is issued for floating objects with a diameter of no more than 2 meters and a speed of no more than 1 meter per second, and drones will be dispatched to handle them. An orange alert is issued for floating objects with a diameter greater than 2 meters and a speed of no more than 1 meter per second. An interception net is activated and unmanned boats are dispatched. A red alert is issued for floating objects with a diameter greater than 2 meters and a speed greater than 1 meter per second, simultaneously triggering an interception net, unmanned vessel, and emergency alarm.

[0016] In the preferred embodiment, the spherical body is made of elastic alloy steel, with a diameter adapted to wind protection requirements. The spherical structure can disperse impact force through its curved surface, reducing the stress intensity in local areas. The anchor chain suction cylinder penetrates vertically into the seabed soil layer, achieving a stable connection with the seabed through the suction effect created by vacuuming. Its cylinder dimensions are designed based on the weight of the spherical body and the geological conditions of the marine area to ensure structural stability under wave impact. The damping buffer layer is made of highly elastic damping material and covers the inner wall of the spherical main body. It absorbs and dissipates impact energy through material deformation, reduces the impact force transmitted to the anchor chain suction cylinder, and reduces the vibration and damage to the foundation structure. The rotation speed adjustment logic of the rotating mechanism is as follows: when the wind speed is low, the rotation speed is maintained at a low speed to reduce energy consumption; when the wind speed increases, the rotation speed increases with the increase of wind turbine power generation. The centrifugal force generated by the rotation helps to push away small floating objects, reduce their continuous contact time with the spherical body, and reduce the cumulative damage caused by repeated impacts.

[0017] In the preferred embodiment, the multi-layered horizontal infrared sensing lines of the infrared touch sensing network are distributed at intervals along the vertical direction to form a three-dimensional sensing area, which can identify floating objects at different heights. After being triggered, it can quickly locate the touch position and transmit precise coordinates to the control center, ensuring accurate capture of the height information of the floating objects. The scanning range of the SAR radar module covers a certain distance of sea area around the wind field and continuously monitors at a fixed period. It can identify floating objects within a certain diameter range and track their movement trajectory, providing long-distance early warning data for the control center. The rotation speed adjustment logic of the rotating mechanism is as follows: when the wind speed is low, the rotation speed is maintained at a low speed to reduce energy consumption; when the wind speed increases, the rotation speed increases with the increase of wind turbine power generation; the centrifugal force generated by the rotation helps to push away small floating objects and reduce their continuous contact time with the spherical body.

[0018] In the preferred embodiment, the unmanned surface vessel is equipped with a grasping device that can adapt to different types of floating objects, possessing grasping, cutting, or towing functions, and can handle large floating objects made of materials such as metal, wood, and plastic; the unmanned aerial vehicle's grasping device has a lightweight structure, suitable for quickly grasping small floating objects, and its lightweight design improves flight efficiency; both maintain real-time data interaction with the control center via wireless communication, providing feedback on the task execution status and ensuring that the control center can monitor the cleanup progress in real time; the electrically operated lifting interception net can adjust its height according to instructions, rising to near the water surface to form a physical barrier during interception, preventing the floating object from continuing to move, and lowering itself underwater when not in operation to reduce water resistance and minimize damage to the net from the marine environment.

[0019] In the preferred embodiment, the decision tree algorithm of the control center uses the diameter and speed of the floating object as core parameters, and determines the risk level by combining the prediction results of its motion trajectory. Different levels correspond to preset equipment linkage strategies to ensure timely and targeted response and avoid resource waste or processing delays.

[0020] In a preferred embodiment, the system further includes an intelligent maintenance module. This module collects real-time equipment operating status data, including structural stress, corrosion level, and circuit continuity, through sensors deployed on the spherical anti-collision device and monitoring network. By analyzing the data, it determines whether the equipment has a fault and the type of fault. For minor faults, it automatically dispatches unmanned equipment to replace components, reducing human intervention. For serious faults, it generates manual repair work orders containing the fault location and preliminary repair plan, improving repair efficiency and accuracy.

[0021] Example: Figure 2 As shown, an operation method for a marine wind farm collision avoidance and floating object handling system includes the following steps: The S1 SAR radar module scans the surrounding sea area of ​​the wind field at a fixed interval of 10 minutes, covering a 5-kilometer radius around the wind field. During the scan, the high-resolution imaging of the X-band synthetic aperture radar and the improved YOLOv5 model identify the position, size, speed, and trajectory of floating objects. Size identification covers floating objects with a diameter of at least 0.3 meters, and it distinguishes between different material types such as plastic, metal, and wood. All identification data is uploaded to the control center in real time and stored. If the SAR radar module detects a floating object but it does not enter the near-field range (i.e., more than 200 meters from the wind field redline), it continuously tracks its trajectory, updating its position and speed data every 10 minutes until the floating object completely leaves the 5-kilometer monitoring range or enters the near-field area to trigger infrared sensing. S2. When a floating object enters the 200-meter range of the wind field red line due to ocean currents or wind, and touches any layer of horizontal infrared sensor wires of the infrared touch sensor network, the local alarm device is immediately triggered. This alarm device is a buzzer that emits a continuous warning sound to alert nearby workers, and can be linked to a light alarm as needed to enhance the warning effect at night or in low visibility conditions; at the same time, the infrared touch sensor network sends a signal containing the precise location, height, and real-time speed of the floating object to the control center within 2 seconds to achieve precise near-field positioning. S3. After receiving the signal, the control center fuses the long-range monitoring data from the SAR radar module with the near-field trigger signal from the infrared touch sensor network. It then uses a decision tree algorithm to classify the risk level of the floating object and activates a preset response strategy according to the corresponding level. S3.1 When a floating object with a diameter of no more than 2 meters and a speed of no more than 1 meter / second is identified as a yellow alert, the control center sends a dispatch command to the drone. The drone navigates to the target location via GPS, uses a suspended net to grab the floating object, and transports it to a designated collection point around the wind farm according to the planned path. After grabbing small floating objects, the drone transmits the task execution status back to the control center via wireless communication, including whether the grab was successful, its current location, and remaining battery power. If the grab fails or the battery is insufficient, the control center can dispatch a backup drone to take over. S3.2 When the diameter of a floating object is greater than 2 meters and its speed is not greater than 1 m / s, an orange alert is issued. The control center simultaneously activates the electric lifting interception net and the unmanned boat: the interception net is raised to near the water surface to form a physical barrier to prevent the floating object from moving further; the unmanned boat arrives at the scene with a robotic arm or towing device. Its robotic arm is equipped with a pressure sensor to avoid breaking the floating object due to excessive gripping force. It selects the gripping, cutting or towing method according to the type of floating object. During the towing process, the optimal path is calculated through PID control algorithm to reduce energy consumption and avoid obstacles such as wind farm pile foundations, and transfer it to the designated area. S3.3 When a floating object has a diameter greater than 2 meters and a speed greater than 1 meter per second, it is considered a red alert. The control center will activate the interception net and unmanned surface vessel, and at the same time trigger the emergency alarm system to send alarm information to the wind farm operation and management platform and nearby maritime departments, and simultaneously display the real-time trajectory of the floating object to facilitate emergency coordination of external rescue forces. The coordination logic of the unmanned surface vessel and the drone is the same as that of the orange alert to ensure rapid response. S4, the intelligent maintenance module continuously monitors the status of the system equipment through sensors deployed on the spherical anti-collision device and monitoring network: S4.1 The stress sensor and corrosion monitoring probe inside the spherical device collect structural stress and surface corrosion data in real time; S4.2 The current monitoring module of the infrared sensing network and the interception network detects the continuity of the circuit and the operating status of the electric components; S4.3 The control center uses AI algorithms to analyze the collected data and diagnose fault types: for minor faults, it automatically dispatches unmanned surface vessels (USVs) or drones carrying spare parts for replacement; for major faults, it generates manual repair work orders containing fault location, fault type, and preliminary repair plan, and pushes them to maintenance personnel terminals. Simultaneously, based on historical equipment fault data, sea wave intensity, and seawater salinity, it dynamically predicts maintenance cycles through machine learning models, correlating equipment runtime, historical fault repair records, and real-time environmental parameters to generate dynamic maintenance plans: equipment maintenance cycles in high sea state areas are shortened to 3-5 years, and in low sea state areas to 5-7 years. When performing cleanup tasks, USVs use onboard cameras and sensors to simultaneously inspect surrounding spherical devices and infrared sensor networks, recording equipment appearance and operating status. This simultaneous inspection data serves as supplementary information for assessing equipment wear. If the wear of the damping buffer layer exceeds 30% or the rotation speed of the rotating mechanism is abnormal, a targeted maintenance process is immediately triggered to further optimize the maintenance plan.

[0022] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention; no reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A collision avoidance and floating object handling system for offshore wind farms, characterized in that: The system includes a ring-shaped protective belt, spherical anti-collision units, a monitoring network, cleaning equipment, and a control center; The annular protective belt includes an array of spherical anti-collision devices arranged at intervals along the wind farm red line; The spherical anti-collision unit consists of an anchor chain suction cylinder and a spherical body installed on top of it. The inner wall of the spherical body is provided with a damping buffer layer, and a rotating mechanism driven by a variable frequency motor is configured inside. The rotating mechanism is connected to a wind turbine generator through a power supply line, and the rotation speed is dynamically adjusted with the wind speed. The monitoring network includes an infrared touch sensing network and an AR radar module; wherein the infrared touch sensing network is composed of multiple layers of horizontal infrared sensing lines connecting adjacent spherical devices, and the SAR radar module is used to scan the sea area surrounding the wind field to identify the position, size, speed and trajectory of floating objects. The cleaning equipment includes unmanned boats, drones, and electrically raised interception nets, wherein the unmanned boats and drones are each equipped with grabbing devices, and the bottom of the electrically raised interception nets is fixed by anchor chains. The control center communicates with the ring-shaped protective belt, spherical anti-collision units, monitoring network, and cleaning equipment. It is configured with a decision tree algorithm to classify risk levels as yellow, orange, and red. A yellow alert is issued for floating objects with a diameter of no more than 2 meters and a speed of no more than 1 meter per second, and drones will be dispatched to handle them. An orange alert is issued for floating objects with a diameter greater than 2 meters and a speed of no more than 1 meter per second. An interception net is activated and unmanned boats are dispatched. A red alert is issued for floating objects with a diameter greater than 2 meters and a speed greater than 1 meter per second, simultaneously triggering an interception net, unmanned vessel, and emergency alarm.

2. The offshore wind farm collision avoidance and floating object handling system according to claim 1, characterized in that, The spherical body is made of elastic alloy steel, with a diameter adapted to wind field protection requirements. The spherical structure can disperse impact force through its curved surface. The anchor chain suction cylinder is vertically inserted into the seabed soil layer and achieves a stable connection with the seabed through the suction effect. Its cylinder size is designed according to the weight of the spherical body and the geological conditions of the sea area. The damping buffer layer is made of highly elastic damping material and covers the inner wall of the spherical body. It absorbs and dissipates impact energy through material deformation, thereby reducing the impact force transmitted to the anchor chain suction cylinder. The rotation speed adjustment logic of the rotating mechanism is as follows: when the wind speed is low, the rotation speed is maintained at a low speed to reduce energy consumption; when the wind speed increases, the rotation speed increases with the increase of wind turbine power generation; the centrifugal force generated by the rotation helps to push away small floating objects and reduce their continuous contact time with the spherical body.

3. The offshore wind farm collision avoidance and floating object handling system according to claim 1, characterized in that, The infrared touch sensing network has multiple layers of horizontal infrared sensing lines distributed vertically at intervals to form a three-dimensional sensing area, which can identify floating objects at different heights. After being triggered, it can quickly locate the touch position and transmit precise coordinates to the control center. The scanning range of the SAR radar module covers a certain distance of sea area around the wind field and continuously monitors at a fixed period. It can identify floating objects within a certain diameter range and track their movement trajectory.

4. The offshore wind farm collision avoidance and floating object handling system according to claim 1, characterized in that, The unmanned surface vessel is equipped with a grasping device that can adapt to different types of floating objects and has the functions of grasping, cutting or towing; the grasping device of the unmanned aerial vehicle is a lightweight structure and is suitable for quickly grasping small floating objects; both maintain real-time data interaction with the control center through wireless communication and provide feedback on the mission execution status; the electric lifting interception net can adjust its height according to instructions, rising to near the water surface to form a physical barrier when intercepting, and lowering to underwater to reduce water flow resistance when not in operation.

5. The offshore wind farm collision avoidance and floating object handling system according to claim 1, characterized in that, The decision tree algorithm in the control center uses the diameter and speed of the floating object as core parameters, and combines the prediction results of its motion trajectory to determine the risk level. Different levels correspond to preset equipment linkage strategies to ensure timely and targeted responses.

6. The offshore wind farm collision avoidance and floating object handling system according to claim 1, characterized in that, The system also includes an intelligent maintenance module, which collects real-time equipment operating status data, including structural stress, corrosion level, and circuit continuity, through sensors deployed on the spherical anti-collision device and monitoring network. By analyzing data, it can determine whether the equipment has a fault and the type of fault. For minor faults, it can automatically dispatch unmanned equipment to replace parts, and for serious faults, it can generate manual repair work orders that include the fault location and preliminary repair plan.

7. A method for operating a marine wind farm collision avoidance and floating object handling system, characterized in that, Includes the following steps: The S1 and SAR radar modules scan the surrounding sea area at fixed intervals to identify floating objects and record their location, size, speed and trajectory. S2. When a floating object enters a certain range of the wind field red line and touches the infrared touch sensor network, the local alarm device is triggered, and at the same time, a signal containing detailed parameters of the floating object is sent to the control center within a short period of time. S3. After receiving the signal, the control center uses a decision tree algorithm to classify the risk level of the floating objects and activates the preset response strategy according to the corresponding level, and dispatches the corresponding equipment to perform the cleanup task. S4, the intelligent maintenance module continuously monitors the status of system equipment, diagnoses faults and schedules maintenance resources based on monitoring data, and dynamically predicts equipment maintenance cycles based on historical data and environmental parameters.

8. The operation method of the offshore wind farm collision avoidance and floating object handling system according to claim 7, characterized in that, In step S1, if the SAR radar module detects a floating object but it does not enter the near field range, it will continuously track its trajectory and update the data until the floating object leaves the monitoring range or enters the near field area; the local alarm device in step S2 is a device that can emit an alarm sound.

9. The operation method of the offshore wind farm collision avoidance and floating object handling system according to claim 7, characterized in that, In step S3, after receiving the dispatch instruction, the UAV navigates to the location of the target floating object, uses its own grasping device to grasp it, and transports it to the designated collection point; when handling large floating objects, the unmanned vessel can choose to use grasping, cutting or towing methods according to the type of floating object to transfer it to the designated area.

10. The operation method of the offshore wind farm collision avoidance and floating object handling system according to claim 7, characterized in that, In step S4, when predicting the maintenance cycle, the intelligent maintenance module takes into account the equipment running time, marine environmental factors and historical failure patterns to generate a dynamic maintenance plan. At the same time, the unmanned vessel will simultaneously inspect the surrounding equipment while performing the cleaning task to improve maintenance efficiency.

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