Intelligent navigation mark and ecological environment cooperative monitoring system for offshore wind power area

Abstract

The invention discloses an intelligent navigation mark and ecological environment cooperative monitoring system for an offshore wind power area, and relates to the technical field of offshore monitoring, the system comprises a plurality of intelligent navigation mark nodes deployed in an offshore wind power plant, at least one gateway node and a monitoring center, the intelligent navigation mark nodes integrate a plurality of monitoring and communication modules, the system maintains a virtual resource map through a gateway node or a specified node, and records information such as a node geographic position, link quality, residual energy and a dynamic role; the intelligent navigation mark nodes periodically broadcast heartbeat packets and dynamically switch roles, an optimal data transmission path tree is initially constructed, and local network reconstruction is started when the nodes fail or links are interrupted; according to the invention, the adaptability and the anti-damage and disaster-tolerant capability of the network are improved, the cooperative monitoring of the navigation safety and the ecological environment is realized, and the reliable transmission of key data is ensured.

Description

Technical Field

[0001] This invention relates to the field of marine monitoring technology, specifically to an intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind power areas. Background Technology

[0002] With the rapid development of the offshore wind power industry and the continuous expansion of wind farm scale, ensuring navigation safety and monitoring the ecological environment in their respective sea areas have become increasingly important. Traditional navigation aids have limited functions, providing only basic navigation assistance, while marine environmental monitoring typically relies on independent buoys or regular patrols. This disconnect between the two systems leads to high management costs and poor data synergy. Especially in offshore wind farm areas far from shore and with complex environments, building a stable, reliable, and collaborative monitoring network that can simultaneously serve navigation safety and ecological protection faces multiple challenges, including difficulties in communication coverage, limited energy supply, and low equipment survivability.

[0003] Existing technologies include several attempts to construct maritime monitoring networks using navigation marks or buoys. For example, existing technologies transmit data between buoys using pre-defined relay rules. However, this method inherently relies on static or pre-calculated paths, making it unable to cope with dynamic changes such as sudden node failures and drastic fluctuations in link quality under harsh maritime environments, resulting in insufficient network robustness. Another example is the aggregation of various monitoring information through a central base station. While this approach achieves information centralization, it heavily relies on a central node and fixed communication links. If the backbone link is interrupted or the central node fails, the entire network may be paralyzed, lacking the ability to autonomously survive and self-heal in distributed scenarios. Furthermore, directly applying general wireless sensor network protocols to this specific scenario often fails to fully consider the characteristics of offshore wind farm networks, such as semi-fixed topology, significant differences in data priority, and strictly limited node energy, leading to high communication overhead, insufficient real-time performance, and uneven energy consumption.

[0004] Therefore, existing technologies have not yet effectively solved the technical problem of how to build an intelligent collaborative network in offshore wind farm areas with weak communication infrastructure and vulnerable nodes, which can still ensure the reliable and real-time transmission of critical monitoring data even when some nodes or links fail dynamically. Specifically, there is a lack of an intrinsic mechanism that enables network nodes to autonomously recognize the environmental state, dynamically adjust their own functions, and intelligently reconstruct data transmission paths based on the global situation.

[0005] In view of this, an innovative system architecture and technical solution is needed to overcome the inherent defects of the existing static relay and centralized control mode, and improve the overall adaptability and disaster recovery capability of the offshore wind farm monitoring network. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of existing technologies and provide an intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind farms. By constructing a dynamic self-organizing monitoring network, it realizes intelligent node role switching and local network reconstruction, which can ensure the reliable and real-time transmission of key monitoring data in harsh environments and effectively solve the problem of coordinated navigation safety and ecological environment monitoring in offshore wind farms.

[0007] To address the aforementioned technical problems, this invention provides the following technical solution: a collaborative monitoring system for intelligent navigation marks and the ecological environment in offshore wind farms, comprising multiple intelligent navigation mark nodes deployed in offshore wind farms, at least one gateway node, and a monitoring center.

[0008] The intelligent navigation beacon node integrates a navigation safety monitoring module, an ecological environment monitoring module, an edge computing module, a multi-mode communication module, and a power management module;

[0009] The gateway node is connected to at least one backbone communication link;

[0010] The system achieves collaborative monitoring and disaster recovery through the following mechanisms:

[0011] The gateway node or designated smart beacon node is configured to maintain and periodically update a virtual resource map covering all smart beacon nodes.

[0012] The virtual resource map records at least the geographical location information of each node, historical link quality data for each communication direction, remaining energy level, and dynamic role information;

[0013] Each of the smart beacon nodes is configured to periodically broadcast a heartbeat packet containing its own status information and dynamically switch between multiple preset roles according to instructions from the gateway node or higher-level nodes in the network.

[0014] The preset roles include at least the acquisition terminal role, the cluster head node role, and the relay backbone node role;

[0015] The system is configured to construct an optimal data transmission path tree based on the virtual resource map in the initial state, with the gateway node as the root node and connecting all smart beacon nodes;

[0016] When the system determines that any network node has failed or the link has been interrupted based on the missing or missing heartbeat packets, the control node initiates a local network reconstruction mechanism based on the latest virtual resource map.

[0017] The local network reconstruction mechanism is as follows: without reconstructing the global path tree, the data backhaul path is dynamically replanned to bypass the fault point or poor link by sending path update instructions to the neighboring nodes of the affected node.

[0018] The system is configured to classify monitoring data and implement differentiated scheduling strategies for data of different priorities in the node's transmission queue.

[0019] When the optimal data transmission path tree cannot be maintained, the system switches to emergency flooding mode, allowing the highest priority data packets to be broadcast between surviving nodes with a limited number of hops until they are received by any available gateway node or the monitoring center.

[0020] Furthermore, the virtual resource map is a multi-dimensional state data structure, and the node state information recorded in the virtual resource map includes:

[0021] Precise coordinates obtained through the Global Navigation Satellite System;

[0022] The wireless link quality index in each direction is calculated by periodically detecting packet loss rate, latency and signal strength in communication with neighboring nodes.

[0023] The current remaining battery capacity and real-time power generation are obtained through a fuel meter and a power sensor;

[0024] The data queue load value representing the current functional load of the node, and the current dynamic role identifier assigned by the control node.

[0025] Furthermore, the dynamic roles include:

[0026] The data acquisition terminal is configured to primarily collect and encapsulate local navigation safety and ecological environment data, and only send the monitoring data it generates.

[0027] The cluster head node role is configured to aggregate data from other nodes that are in the acquisition terminal role within a local area defined by the control node, perform data fusion and compression processing, and manage the path of data uplink from that area to the gateway node.

[0028] The relay backbone node role is configured to specifically undertake cross-regional and long-distance data forwarding tasks, serving as a key relay hub in the optimal data transmission path tree;

[0029] The sleeping role is configured to shut down unnecessary functional modules and enter a low-power listening state when in areas of network redundancy or when its own energy is below the warning threshold.

[0030] Furthermore, the election or assignment of the cluster head node role is calculated based on a comprehensive weight function. The control node selects the node with the highest comprehensive weight to serve as the cluster head node. The comprehensive weight function is expressed as:

[0031]

[0032] in, Represents a node The overall weight, Represents a node The current remaining energy, This represents the maximum remaining energy of all nodes in the system, used for... Normalization is performed. These are the preset weighting coefficients for the energy term. Represents a node The average of the link quality indices of all neighboring nodes recorded in the virtual resource map. This is the theoretical maximum value of the link quality index, used to evaluate... Normalization is performed. These are the preset weighting coefficients for the link quality item. Represents a node The distance to the geometric center of the predefined local region it is located at. The maximum possible distance within this area is used for... Normalization is performed. The preset weighting coefficients for the location centrality term, and satisfying the following conditions: .

[0033] Furthermore, the specific process of the local network reconstruction mechanism includes:

[0034] After receiving a link warning or detecting a missing heartbeat packet, the control node uses the virtual resource map as input to temporarily remove the faulty node or its poor-quality link from the current network topology model.

[0035] Subsequently, in the affected local subgraph, the shortest path algorithm is run to recalculate one or more alternative paths to the gateway node or the nearest cluster head node for the affected upstream and downstream nodes.

[0036] After the calculation is completed, the control node unicasts or multicasts a path update command containing information about the new next-hop node to the affected nodes. Upon receiving the command, the affected nodes update their local routing tables, and then network data flows through the updated path, thereby completing this local network reconstruction.

[0037] Furthermore, the classification of monitoring data and the implementation of differentiated scheduling strategies for data of different priorities in the node's transmission queue are specifically achieved through the following methods:

[0038] Ship collision warning data is marked as top priority data, equipment displacement alarm and ecological environment parameter exceeding alarm data are marked as first priority data, periodic ecological environment monitoring data are marked as second priority data, and equipment status log and program package data are marked as third priority data.

[0039] In the same node's transmission queue, top-priority data has absolute priority for transmission and can interrupt low-priority data packets that are being transmitted. First-priority data takes precedence over second- and third-priority data. When a node acts as a relay, it must prioritize forwarding top-priority and first-priority data from other nodes.

[0040] Furthermore, the multimode communication module includes a wireless self-organizing network unit for high-speed data transmission and a low-power wide-area network unit for low-power wide-area communication.

[0041] The wireless self-organizing network unit operates in the ultra-high frequency or very high frequency band and supports mesh network networking.

[0042] The low-power wide-area network unit employs long-range radio technology;

[0043] The system uses the wireless ad hoc network unit for data transmission by default. When the link quality of the wireless ad hoc network unit is continuously lower than the first threshold, the low-power wide area network unit is automatically enabled to transmit link status control signaling.

[0044] Furthermore, the heartbeat packets periodically broadcast by the intelligent beacon node contain at least the following self-state information: node identifier, global navigation satellite system coordinates, real-time link quality measurement values ​​of the wireless ad hoc network unit and the low-power wide area network unit, remaining battery percentage, current data queue load value, and the dynamic role currently being played.

[0045] Furthermore, the monitoring center is configured to receive and integrate data from all gateway nodes, run the global view generation and maintenance algorithm of the virtual resource map, visualize the spatiotemporal distribution of the entire network status, navigation safety situation and ecological environment parameters, and has the ability to issue configuration instructions and tasks to designated smart navigation beacon nodes or the entire network.

[0046] Furthermore, the transmission delay of the top priority data is required to be less than 1 second, the transmission delay of the first priority data is required to be less than 10 seconds, the second priority data is allowed to have a transmission delay on the order of minutes, and the third priority data has no real-time transmission requirement.

[0047] In the emergency flooding mode, only top-priority data and first-priority data are allowed to be broadcast, and the number of broadcast hops does not exceed a preset maximum value.

[0048] Compared with existing technologies, this intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind farms has the following advantages:

[0049] I. This invention maintains and updates a virtual resource map covering all nodes through gateway nodes or designated smart beacon nodes. Combined with the periodic broadcast heartbeat packets and dynamic role switching mechanism of smart beacon nodes, it constructs an optimal data transmission path tree with the gateway node as the root node. When a node fails or a link is interrupted, it initiates local network reconstruction. Alternative paths can be planned without global reconstruction. This solves the problem that the network is unable to cope with sudden node failures and link quality fluctuations in offshore wind farm areas under the existing static relay and centralized control modes. It enables network nodes to autonomously recognize the environmental status and dynamically adjust their functions, significantly improving the adaptability and disaster recovery capabilities of the monitoring network, and ensuring the reliable and real-time transmission of key monitoring data.

[0050] Second, this invention optimizes network resource allocation and energy utilization efficiency by classifying monitoring data and implementing differentiated scheduling strategies, combined with adaptive switching of multi-mode communication modules and low-power design of dormant roles. Priority transmission of top-priority and first-priority data ensures timely feedback of emergency information, while low-priority data is transmitted when the network is idle to avoid resource waste. Dormant roles effectively reduce energy consumption in redundant areas or low-energy nodes and extend node lifespan.

[0051] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0053] Figure 1 This is a schematic diagram of the overall system architecture and data flow of the present invention;

[0054] Figure 2 This is a schematic diagram of the local network reconstruction and emergency flooding mechanism of the present invention;

[0055] Figure 3 This is a schematic diagram of the dynamic role switching and cluster head election mechanism of the present invention. Detailed Implementation

[0056] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0057] Example 1

[0058] like Figures 1 to 3 As shown in the figure, this embodiment discloses a specific implementation of an intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind farms. It is applicable to navigation safety assurance and comprehensive ecological environment monitoring scenarios for large-scale offshore wind farms in nearshore areas. The system will be described in detail below with specific technical details.

[0059] In this embodiment, the offshore wind farm is located in the eastern nearshore waters, covering an area of ​​approximately 50 square kilometers. Fifty intelligent navigation beacon nodes are evenly deployed within the farm, and three gateway nodes are deployed along the wind farm's shoreline. The monitoring center is located within a shore-based control station. The intelligent navigation beacon nodes are distributed around the wind turbines, along both sides of the waterway, and in ecologically sensitive areas. The gateway nodes establish a stable connection with the monitoring center via a fiber optic backbone communication link, forming a three-tiered architecture of sensing nodes, gateways, and monitoring center, achieving full coverage monitoring of the entire wind farm's sea area.

[0060] In this embodiment, the intelligent navigation beacon node adopts an integrated sealed design, with its outer shell made of 316L stainless steel and possessing an IP68 protection rating. This allows it to withstand the corrosion of harsh marine environments such as high humidity, high salt spray, and strong winds and waves, ensuring long-term stable operation of the node. The node integrates a navigation safety monitoring module, an ecological environment monitoring module, an edge computing module, a multi-mode communication module, and a power management module. The specific implementations of each module are as follows:

[0061] 1. Navigation Safety Monitoring Module: This module integrates a GPS and BeiDou dual-mode positioning module, a microwave radar sensor, and a beacon attitude sensor. The GPS and BeiDou dual-mode positioning module, as a concrete implementation of the global navigation satellite system, achieves a positioning accuracy of ±1 meter and acquires the node's precise coordinates in real time. The microwave radar sensor has a detection range of 0-3000 meters and a detection angle of 120°, enabling real-time capture of information such as the distance, heading, and speed of surrounding vessels. The beacon attitude sensor monitors the node's tilt angle and sway amplitude; when the tilt angle exceeds a preset threshold, it is determined to be a risk of equipment displacement. This module, through multi-sensor fusion, achieves comprehensive collection of navigation safety-related data, providing safety early warning support for ship navigation.

[0062] 2. Ecological Environment Monitoring Module: This module integrates water quality sensors, meteorological sensors, and marine bioacoustic detectors. The water quality sensors monitor four core parameters: dissolved oxygen, pH, turbidity, and salinity, with measurement accuracies of ±0.1 mg / L, ±0.01 pH, ±1 NTU, and ±0.1‰, respectively. The meteorological sensors monitor wind speed, wind direction, air temperature, and relative humidity. The wind speed measurement range is 0-60 m / s, the wind direction measurement range is 0-360°, the air temperature measurement range is -40℃-85℃, and the relative humidity measurement range is 0-100% RH. The marine bioacoustic detector uses the 100 kHz-1 MHz frequency band to capture activity signals from small and medium-sized marine organisms. This module collects ecological environment data at preset intervals, providing data support for marine ecological protection.

[0063] 3. Edge Computing Module: Utilizing an ARM Cortex-M7 low-power microprocessor with a clock speed of 216MHz, equipped with 512KB RAM and 8MB Flash storage, this module possesses data processing, fusion, compression, and simple algorithm execution capabilities. It can perform local preprocessing on collected navigation safety and environmental data, such as removing abnormal sensor data, calculating parameter averages over a specific time period, and compressing data using the LZ77 compression algorithm to reduce bandwidth consumption and energy consumption in subsequent data transmission.

[0064] 4. Multimode Communication Module: This module includes a wireless ad-hoc network (WAN) unit and a low-power wide-area network (LPWAN) unit. The WNA unit operates in the 433MHz UHF band, supports the Mesh networking protocol, has a communication rate of 250kbps, a single-hop communication distance of up to 500 meters, and supports multi-hop coverage extension, making it suitable for high-speed, short-distance data transmission between nodes. The LWAN unit uses LoRa long-range radio technology, operates in the 915MHz band, has a communication rate of 0.3kbps-50kbps, a single-hop communication distance of up to 3 kilometers, low power consumption, and strong anti-interference capabilities, making it suitable for low-speed, long-distance link status control signaling transmission. The system defaults to prioritizing the WNA unit for data transmission. When the link quality index of the WNA unit remains below 40 for three consecutive monitoring cycles, it automatically switches to the LWAN unit to transmit link status control signaling, ensuring the continuity of the communication link.

[0065] 5. Power Management Module: Employs a hybrid power supply scheme combining solar panels and lithium-ion battery packs. The solar panels have a power output of 30W and are equipped with a maximum power point tracking controller to improve solar energy conversion efficiency. The lithium-ion battery pack has a capacity of 100Ah, uses lithium iron phosphate batteries, and features long cycle life and high safety. The module incorporates a fuel gauge and power sensor to collect real-time data on the remaining battery capacity and the real-time power output of the solar panels, providing data for power management and node role adjustment. Simultaneously, the module features overcharge, over-discharge, and overcurrent protection functions to ensure the safety and stability of the node's energy supply.

[0066] In this embodiment, the gateway node adopts an industrial-grade communication gateway hardware platform, equipped with a multi-core processor and a large-capacity storage unit, supporting multi-link redundancy design. Each gateway node is simultaneously connected to both the fiber optic backbone communication link and the 4G / 5G mobile network link. When one of the backbone communication links is interrupted, it automatically switches to the other link to ensure uninterrupted communication with the monitoring center. The communication interface of the gateway node supports adaptation to the wireless self-organizing network unit and low-power wide area network unit of the smart beacon node, and can receive monitoring data from the smart beacon node, upload it to the monitoring center after preliminary aggregation, and simultaneously receive configuration instructions and control instructions issued by the monitoring center and forward them to the corresponding smart beacon node.

[0067] In this embodiment, the monitoring center deploys a server cluster, a data storage array, a visualization terminal, and a command issuing terminal. The server cluster runs algorithms for generating and maintaining a global view of a virtual resource map, data fusion analysis, and network status monitoring. The data storage array adopts a distributed storage architecture with a capacity of 100TB, used to store all monitoring data, node status data, and system operation logs, with a storage period of 3 years. The visualization terminal displays the geographical distribution, remaining energy status, link quality, navigation safety status, and spatiotemporal distribution of ecological and environmental parameters of all network nodes in real time through a graphical interface, supporting historical data backtracking and trend analysis. The command issuing terminal is operated by administrators, who can issue configuration commands to designated smart navigation beacon nodes or all network nodes, such as adjusting the data collection cycle, modifying role switching thresholds, and updating priority scheduling parameters.

[0068] In this embodiment, the collaborative monitoring and disaster recovery mechanism is implemented as follows:

[0069] The specific implementation of maintaining and updating the virtual resource map is as follows:

[0070] Three gateway nodes are designated to jointly undertake the maintenance of the virtual resource map, employing a master-slave failover mechanism to ensure the continuity of map maintenance. The virtual resource map is a multi-dimensional state data structure, and the recorded node state information and its acquisition methods are as follows:

[0071] 1. Precise coordinates: The coordinates are collected by the GPS and Beidou dual-mode positioning module of the smart navigation beacon node. The collection period is 10 seconds. After the collected data is verified by the edge computing module, it is sent to the gateway node via a heartbeat packet.

[0072] 2. Wireless Link Quality Index in Each Direction: Every 30 seconds, the intelligent beacon node sends a link probe packet to all neighboring nodes. The probe packet contains the node identifier and a sending timestamp. Upon receiving the probe packet, neighboring nodes immediately return a response packet, containing a receiving timestamp and a signal strength value. The sending node calculates the latency based on the sending time of the probe packet and the receiving time of the response packet, calculates the packet loss rate based on the number of probe packet transmissions and response packet receptions, and combines this with the signal strength value to calculate the wireless link quality index in each direction. The link quality index ranges from 0 to 100, with higher values ​​indicating better link quality. The theoretical maximum value is... .

[0073] 3. Current remaining battery capacity and real-time power generation: Data is collected via the power management module's fuel gauge and power sensor, with a collection period of 60 seconds. The collected data is directly incorporated into the heartbeat packet and sent. This represents the maximum remaining energy of all nodes in the system. The rated capacity of the lithium battery pack is 100Ah.

[0074] 4. Data queue load value and dynamic role identifier: The data queue load value is calculated by the edge computing module to count the number of data items to be sent, with a value range of 0-100; the dynamic role identifier is assigned by the gateway node according to the node status and is updated in real time as the role changes. It is sent to the node through an instruction, and the node includes it in the heartbeat packet feedback.

[0075] The gateway node aggregates the heartbeat data of all smart beacon nodes every minute and updates the virtual resource map. The updated map is then synchronized to all smart beacon nodes via multicast, ensuring that all nodes in the network work collaboratively based on a unified state view.

[0076] The specific implementation of heartbeat packet broadcasting and dynamic role switching is as follows:

[0077] 1. Heartbeat Packet Broadcast: Each smart beacon node broadcasts a heartbeat packet every 20 seconds. The heartbeat packet uses a simplified data format, with a total length not exceeding 64 bytes. It includes the node's status information, specifically: node identifier, GPS and BeiDou dual-mode positioning coordinates, wireless ad hoc network unit link quality index, low-power wide area network unit link quality index, remaining battery percentage, current data queue load value, and current dynamic role identifier. The broadcast power of the heartbeat packet is dynamically adjusted based on the node's remaining energy. Standard power is used when remaining energy is sufficient, and the broadcast power is reduced when remaining energy is low to minimize energy consumption.

[0078] 2. Dynamic Role Switching: The intelligent beacon node dynamically switches between the roles of data acquisition terminal, cluster head node, relay backbone node, and dormant node according to the instructions of the gateway node. The switching triggering conditions and implementation process are as follows:

[0079] Data Acquisition Terminal Role: Initially, all smart beacon nodes assume this role, primarily performing local data acquisition and encapsulation. They only send their own generated monitoring data and do not participate in forwarding or aggregating data from other nodes. This role is suitable for densely populated areas or nodes with limited energy reserves.

[0080] Cluster head node role: The gateway node divides the entire wind farm into 5 local areas, each containing 10 smart navigation nodes. It calculates the comprehensive weight of each node in a 30-minute cycle using a comprehensive weight function, and selects the node with the highest comprehensive weight to serve as the cluster head node.

[0081] The expression for the comprehensive weighting function is:

[0082]

[0083] in, , , As a preset weighting coefficient, this embodiment selects... , , ,satisfy This value takes into account both the sustainability of node energy and the stability of link quality and the centrality of location. For nodes The current remaining energy, This represents the maximum remaining energy of all nodes in the system. For nodes The average of the link quality index of all neighboring nodes. This represents the theoretical maximum value of the link quality index. For nodes The distance to the geometric center of its local region; This represents the maximum possible distance within the region.

[0084] Once the cluster head node is selected, the gateway node issues a cluster head activation command. After receiving the command, the node starts the data aggregation function, receives data from other data collection terminal nodes in the area through the multi-mode communication module, performs data fusion and compression using the edge computing module, selects the optimal uplink path based on the virtual resource map, and uploads the processed data to the gateway node.

[0085] Relay backbone node role: Based on the virtual resource map, gateway nodes select nodes geographically located at regional boundaries, with a link quality index ≥ 80 and remaining energy ≥ 60% as relay backbone nodes. Two relay backbone nodes are set up in each region, specifically to undertake cross-regional, long-distance data forwarding tasks. After receiving the role assignment instruction from the gateway node, the relay backbone nodes disable some unnecessary local data collection functions, increase the work priority of the communication module, and ensure the efficiency of data forwarding.

[0086] Sleeping Role: When a node is in a network redundancy area or its remaining battery percentage is below 20%, the gateway node issues a sleep command. Upon receiving the command, the node shuts down the marine organism acoustic detector and the wireless ad hoc network unit in the ecological environment monitoring module, retaining only the GPS and BeiDou dual-mode positioning module, attitude sensor, low-power wide area network unit, and power management module. It then enters a low-power listening state with a listening cycle of 30 seconds. When it receives a wake-up command or its remaining energy recovers to above 30%, it exits the sleep state and resumes normal function.

[0087] The specific implementation of constructing the optimal data transmission path tree is as follows:

[0088] Initially, the gateway node, based on a virtual resource map, uses Dijkstra's shortest path algorithm to construct an optimal data transmission path tree connecting all smart beacon nodes, with the gateway node as the root node. The evaluation metrics for path selection include link quality index, node remaining energy, and transmission hop count, with evaluation weights of 0.5, 0.3, and 0.2, respectively. The specific construction process is as follows: starting from the gateway node, all smart beacon nodes are traversed, the comprehensive path cost from each node to the gateway node is calculated, and the path with the lowest comprehensive path cost is selected as the optimal data transmission path for that node, ultimately forming a path tree covering the entire network. After the path tree is constructed, the gateway node sends the next-hop node information of each node to the corresponding node, and the nodes store this information in their local routing tables.

[0089] The specific implementation of the local network reconstruction mechanism is as follows:

[0090] If a gateway node does not receive a heartbeat packet from a node for more than 3 cycles, or receives a link quality warning message from a node, it determines that the node is faulty or the link is interrupted, and initiates a local network reconstruction mechanism. The specific process is as follows:

[0091] 1. Fault Isolation: The gateway node uses the latest virtual resource map as input to temporarily remove faulty nodes or poor-quality links from the current network topology model and mark them as unavailable.

[0092] 2. Alternative path calculation: In the affected local subgraph, run Dijkstra's shortest path algorithm to recalculate one or more alternative paths to the gateway node or the nearest cluster head node for the affected upstream and downstream nodes. The alternative paths must meet the conditions of link quality index ≥ 50 and node remaining energy ≥ 30%.

[0093] 3. Path update command issuance: The gateway node will send a path update command containing the new next-hop node identifier, path priority, and transmission parameters to the affected upstream and downstream nodes via multicast.

[0094] 4. Routing Table Update and Data Transmission: Upon receiving a path update command, affected nodes update their local routing tables within one second. Subsequent data transmission follows the updated path. For example, if node SN025 fails, its upstream nodes SN023 and SN024 cannot transmit data via the original path. The gateway node recalculates the path, instructing SN023 to forward the data to cluster head node SN030 via SN026 and SN027, and SN024 to forward the data to cluster head node SN030 via SN028. After SN023, SN024, SN026, SN027, and SN028 update their routing tables, data is transmitted normally via the new path, completing the local network reconstruction.

[0095] This mechanism eliminates the need for global path tree reconstruction, adjusting paths only for affected local areas. The reconstruction time is kept within one minute, effectively reducing network overhead and ensuring the continuity of data transmission.

[0096] In this embodiment, the specific implementation of hierarchical and differentiated scheduling of monitoring data is as follows:

[0097] The system classifies monitoring data into four levels, and the specific criteria and scheduling strategies for different priority data are as follows:

[0098] 1. Top Priority Data: Ship collision warning data, i.e., warning data generated when the microwave radar sensor detects a ship less than 500 meters away from the node. This type of data requires a transmission delay of less than 1 second and has absolute priority in the node's transmission queue. If a node is currently transmitting low-priority data, it can immediately interrupt the transmission of low-priority data to prioritize the transmission of top priority data. When a node acts as a relay, it must forward top priority data within 100 milliseconds without delay.

[0099] 2. First-priority data: Equipment displacement alarm data and ecological environment parameter exceeding alarm data. The transmission delay of this type of data is required to be less than 10 seconds. It has a higher priority than second- and third-priority data in the transmission queue and is only sent when there is no special-priority data. When a node acts as a relay, it must prioritize forwarding this type of data, and the forwarding delay shall not exceed 500 milliseconds.

[0100] 3. Second-level priority data: Periodic ecological environment monitoring data, collected and generated on a 5-minute cycle. This type of data allows for minute-level transmission delays. Its priority in the transmission queue is lower than that of first-level priority data. It is only sent when there is no special-level or first-level priority data. The transmission rate can be adjusted according to the link status during forwarding.

[0101] 4. Level 3 Priority Data: Device status log data and program package data. This type of data does not have real-time transmission requirements, has the lowest priority in the transmission queue, and is transmitted only when the network is idle. It can also be transmitted in fragments to avoid consuming too many communication resources.

[0102] In this implementation, the specific implementation of triggering and operating the emergency flooding mode is as follows:

[0103] When the gateway node detects that more than 30% of the smart beacon nodes have lost connection with the gateway node, and the local network reconstruction cannot restore the main data transmission path, it determines that the optimal data transmission path tree cannot be maintained, and the system switches to emergency flooding mode.

[0104] In emergency flooding mode, only top-priority and first-priority data are allowed to be broadcast. The maximum broadcast hop count is preset to 3 hops, meaning that after a data packet is sent from the source node, it will be forwarded through a maximum of 3 surviving nodes. If it is not received by the gateway node, it will be automatically discarded to avoid network congestion caused by unlimited broadcasting. For example, if a gateway node in a certain area fails due to extreme weather, causing 10 smart navigation beacon nodes in that area to lose connection with the monitoring center, after the system switches to emergency flooding mode, the ship collision warning data and ecological environment exceedance alarm data generated by these nodes will be received by the gateway nodes in adjacent areas after a maximum of 3 hops through broadcast forwarding among surviving nodes, and finally uploaded to the monitoring center, ensuring that critical alarm data is not lost. When the failed gateway node recovers or the main data transmission path is rebuilt, the system automatically exits emergency flooding mode and reverts to the optimal data transmission path tree mode.

[0105] This embodiment, through the above system configuration and mechanism design, realizes the coordinated monitoring of navigation safety and ecological environment in offshore wind power areas, effectively solving the problems of unstable network communication, limited energy, and weak resilience in offshore wind power area monitoring networks, and achieving the coordinated advancement of navigation safety assurance and ecological environment monitoring.

[0106] Example 2

[0107] like Figures 2 to 3 As shown in Example 1, this example elaborates on the specific steps of a smart navigation mark and ecological environment collaborative monitoring system for offshore wind farms during operation. The specific steps are as follows:

[0108] 1. System Deployment Phase: Install smart navigation beacon nodes in designated areas of the offshore wind farm, deploy gateway nodes along the coastline, complete the installation of hardware equipment and software system deployment for the monitoring center, establish the backbone communication link between the gateway nodes and the monitoring center, and initialize the configuration of all smart navigation beacon nodes, including node identifier allocation, communication parameter settings, and data acquisition cycle settings.

[0109] 2. Virtual Resource Map Initialization: After the smart beacon node is started, it obtains its own precise coordinates through the global navigation satellite system, detects neighboring nodes and establishes communication connections through the multi-mode communication module, collects initial link quality data and remaining energy data, generates initial status information and sends it to the gateway node through heartbeat packets; the gateway node summarizes the initial status information of all nodes, constructs the initial virtual resource map, and synchronizes it to all nodes in the network.

[0110] 3. Construction of the optimal data transmission path tree: Based on the initial virtual resource map, the gateway node uses Dijkstra's shortest path algorithm to calculate the optimal path from each smart beacon node to the gateway node, forming the optimal data transmission path tree. The next-hop information of each node is sent to the corresponding node, and the node updates its local routing table.

[0111] 4. Dynamic Role Assignment: Based on the node status information in the virtual resource map, the gateway node calculates the comprehensive weight of each node through a comprehensive weight function, divides local areas and designates cluster head nodes, selects nodes that meet the conditions as relay backbone nodes, and issues dormant commands to network redundant areas or low-energy nodes to complete the initial role assignment.

[0112] 5. Data Acquisition and Transmission: Intelligent navigation beacon nodes collect data according to a preset cycle through the navigation safety monitoring module and the ecological environment monitoring module. After preprocessing by the edge computing module, the data is transmitted according to its own role. Terminal nodes directly send the data they have collected; cluster head nodes aggregate data within their region, fuse and compress it, and then upload it; relay backbone nodes forward cross-regional data; and all data is transmitted to the gateway node along the optimal data transmission path tree according to a priority scheduling strategy, and then uploaded to the monitoring center by the gateway node.

[0113] 6. Virtual Resource Map Update: Smart beacon nodes periodically broadcast heartbeat packets, and gateway nodes summarize the heartbeat packet data every minute, update the virtual resource map, and synchronize it to all nodes in the network to ensure the real-time status information of nodes.

[0114] 7. Network Status Monitoring and Fault Handling: The system monitors heartbeat packet transmission and link quality data in real time. When a node failure or link interruption is detected, a local network reconstruction mechanism is initiated to replan alternative paths and update the node routing table. When the optimal data transmission path tree cannot be maintained, the system switches to emergency flooding mode to ensure the transmission of critical data.

[0115] 8. Dynamic Role Adjustment: Every 30 minutes, the gateway node recalculates the overall weight of each node based on the updated virtual resource map, and adjusts the distribution of cluster head nodes, relay backbone nodes, and dormant nodes to achieve dynamic optimization of node functions and balance network energy consumption.

[0116] 9. Data Processing and Display: The monitoring center receives monitoring data uploaded by gateway nodes, integrates, analyzes and stores the data, and displays the overall network status, navigation safety situation and spatiotemporal distribution of ecological environment parameters through a visualization terminal. Management personnel issue configuration adjustment instructions through the instruction distribution terminal according to the monitoring situation.

[0117] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A smart navigation mark and ecological environment collaborative monitoring system for offshore wind power areas, characterized in that, This includes multiple smart navigation beacon nodes deployed at offshore wind farms, at least one gateway node, and a monitoring center: The intelligent navigation beacon node integrates a navigation safety monitoring module, an ecological environment monitoring module, an edge computing module, a multi-mode communication module, and a power management module; The gateway node is connected to at least one backbone communication link; The system achieves collaborative monitoring and disaster recovery through the following mechanisms: The gateway node or designated smart beacon node is configured to maintain and periodically update a virtual resource map covering all smart beacon nodes. The virtual resource map records at least the geographical location information of each node, historical link quality data for each communication direction, remaining energy level, and dynamic role information; Each of the smart beacon nodes is configured to periodically broadcast a heartbeat packet containing its own status information and dynamically switch between multiple preset roles according to instructions from the gateway node or higher-level nodes in the network. The preset roles include at least the acquisition terminal role, the cluster head node role, and the relay backbone node role; The system is configured to construct an optimal data transmission path tree based on the virtual resource map in the initial state, with the gateway node as the root node and connecting all smart beacon nodes; When the system determines that any network node has failed or the link has been interrupted based on the missing or missing heartbeat packets, the control node initiates a local network reconstruction mechanism based on the latest virtual resource map. The local network reconstruction mechanism is as follows: without reconstructing the global path tree, the data backhaul path is dynamically replanned to bypass the fault point or poor link by sending path update instructions to the neighboring nodes of the affected node. The system is configured to classify monitoring data and implement differentiated scheduling strategies for data of different priorities in the node's transmission queue. When the optimal data transmission path tree cannot be maintained, the system switches to emergency flooding mode, allowing the highest priority data packets to be broadcast between surviving nodes with a limited number of hops until they are received by any available gateway node or the monitoring center.

2. The intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind power areas according to claim 1, characterized in that, The virtual resource map is a multi-dimensional state data structure, and the node state information recorded in the virtual resource map includes: Precise coordinates obtained through the Global Navigation Satellite System; The wireless link quality index in each direction is calculated by periodically detecting packet loss rate, latency and signal strength in communication with neighboring nodes. The current remaining battery capacity and real-time power generation are obtained through a fuel meter and a power sensor; The data queue load value representing the current functional load of the node, and the current dynamic role identifier assigned by the control node.

3. The intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind power areas according to claim 1, characterized in that, The dynamic roles include: The data acquisition terminal is configured to primarily collect and encapsulate local navigation safety and ecological environment data, and only send the monitoring data it generates. The cluster head node role is configured to aggregate data from other nodes that are in the acquisition terminal role within a local area defined by the control node, perform data fusion and compression processing, and manage the path of data uplink from that area to the gateway node. The relay backbone node role is configured to specifically undertake cross-regional and long-distance data forwarding tasks, serving as a key relay hub in the optimal data transmission path tree; The sleeping role is configured to shut down unnecessary functional modules and enter a low-power listening state when in areas of network redundancy or when its own energy is below the warning threshold.

4. The intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind power areas according to claim 3, characterized in that, The election or assignment of the cluster head node role is based on a comprehensive weight function. The control node selects the node with the highest comprehensive weight to serve as the cluster head node. The comprehensive weight function is expressed as follows: in, Represents a node The overall weight, Represents a node The current remaining energy, This represents the maximum remaining energy of all nodes in the system, used for... Normalization is performed. These are the preset weighting coefficients for the energy term. Represents a node The average of the link quality indices of all neighboring nodes recorded in the virtual resource map. This is the theoretical maximum value of the link quality index, used to evaluate... Normalization is performed. These are the preset weighting coefficients for the link quality item. Represents a node The distance to the geometric center of the predefined local region it is located at. The maximum possible distance within this area is used for... Normalization is performed. The preset weighting coefficients for the location centrality term, and satisfying the following conditions: .

5. The intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind power areas according to claim 1, characterized in that, The specific process of the local network reconstruction mechanism includes: After receiving a link warning or detecting a missing heartbeat packet, the control node uses the virtual resource map as input to temporarily remove the faulty node or its poor-quality link from the current network topology model. Subsequently, in the affected local subgraph, the shortest path algorithm is run to recalculate one or more alternative paths to the gateway node or the nearest cluster head node for the affected upstream and downstream nodes. After the calculation is completed, the control node unicasts or multicasts a path update command containing information about the new next-hop node to the affected nodes. Upon receiving the command, the affected nodes update their local routing tables, and then network data flows through the updated path, thereby completing this local network reconstruction.

6. The intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind power areas according to claim 1, characterized in that, The process of classifying monitoring data and implementing differentiated scheduling strategies for data of different priorities in the node's transmission queue is specifically achieved through the following methods: Ship collision warning data is marked as top priority data, equipment displacement alarm and ecological environment parameter exceeding alarm data are marked as first priority data, periodic ecological environment monitoring data are marked as second priority data, and equipment status log and program package data are marked as third priority data. In the same node's transmission queue, top-priority data has absolute priority for transmission and can interrupt low-priority data packets that are being transmitted. First-priority data takes precedence over second- and third-priority data. When a node acts as a relay, it must prioritize forwarding top-priority and first-priority data from other nodes.

7. The intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind power areas according to claim 1, characterized in that, The multi-mode communication module includes a wireless self-organizing network unit for high-speed data transmission and a low-power wide-area network unit for low-power wide-area communication. The wireless self-organizing network unit operates in the ultra-high frequency or very high frequency band and supports mesh network networking. The low-power wide-area network unit employs long-range radio technology; The system uses the wireless ad hoc network unit for data transmission by default. When the link quality of the wireless ad hoc network unit is continuously lower than the first threshold, the low-power wide area network unit is automatically enabled to transmit link status control signaling.

8. The intelligent navigation mark and ecological environment collaborative monitoring system for offshore wind power areas according to claim 1, characterized in that, The heartbeat packets periodically broadcast by the intelligent navigation beacon nodes contain at least the following self-state information: node identifier, global navigation satellite system coordinates, real-time link quality measurements of wireless ad hoc network units and low-power wide area network units, remaining battery percentage, current data queue load value, and the dynamic role currently being played.

9. A smart navigation mark and ecological environment collaborative monitoring system for offshore wind power areas according to claim 1, characterized in that, The monitoring center is configured to receive and integrate data from all gateway nodes, run the global view generation and maintenance algorithm of the virtual resource map, visualize the spatiotemporal distribution of the entire network status, navigation safety situation and ecological environment parameters, and has the ability to issue configuration instructions and tasks to designated smart navigation beacon nodes or the entire network.

10. A smart navigation mark and ecological environment collaborative monitoring system for offshore wind power areas according to claim 1 or 6, characterized in that, The transmission delay of the top priority data is required to be less than 1 second, the transmission delay of the first priority data is required to be less than 10 seconds, the transmission delay of the second priority data is allowed to be on the order of minutes, and the third priority data has no real-time transmission requirement. In the emergency flooding mode, only top-priority data and first-priority data are allowed to be broadcast, and the number of broadcast hops does not exceed a preset maximum value.

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