An intelligent monitoring system for sediment transport for offshore wind farms

Abstract

The present application relates to the technical field of marine environment monitoring, in particular to a sediment transport intelligent monitoring system for offshore wind farms, comprising: a seabed base module, a sea level buoy module and an optical-electric composite cable connecting the two, the bottom of the buoy module is provided with a sensor cabin with built-in multiple sensors and counterweights, and the base and the buoy module are both equipped with acoustic Doppler current profiler, turbidity sensors and other detection components. The buoy module contains independent watertight compartments, photovoltaic power supply and control components, can identify the sediment transport state through eigenvector analysis and Mahalanobis distance clustering algorithm, intelligently switch three monitoring modes of normal, event triggering and decay tracking, and dynamically adjust the sampling frequency. The system realizes three-dimensional monitoring of the whole process of sediment "suspension-transportation-settlement" and real-time data transmission, solves the limitations of traditional seabed monitoring, takes into account the monitoring accuracy and energy efficiency, and provides reliable support for the safe operation and maintenance of wind farms.

Description

Technical Field

[0001] This invention relates to the field of marine environmental monitoring technology, and more specifically, to an intelligent monitoring system for sediment transport in offshore wind farms. Background Technology

[0002] With the advancement of the global energy transition, offshore wind power has developed rapidly as a clean energy source. However, the construction and operation of wind farms significantly alter the marine dynamic environment, and the resulting sediment transport issues have become a key hidden danger to engineering safety and ecological sustainability. Wind turbine foundations can disturb local flow fields, exacerbate seabed erosion and form scour pits, threatening the structural stability of wind turbines. Turbulent water flows can cause sediment resuspension, forming plumes that affect water quality and benthic ecosystems. Under extreme sea conditions, they can also induce large-scale seabed erosion and sand wave migration, posing geological disaster risks to cable laying and long-term operation. Therefore, precise and long-term monitoring of sediment transport is urgently needed.

[0003] The current mainstream monitoring method is the seabed-based monitoring system, which constructs a seabed observation platform by equipping it with sensors such as resistivity probes and acoustic Doppler current profilers. However, it has obvious drawbacks: First, the bottom-mounted design can only efficiently monitor the near-bottom boundary layer and cannot track the three-dimensional diffusion path and range of sediment plumes transported to the middle and upper layers of the water body. Second, it adopts a "storage-recovery" working mode, resulting in serious data acquisition delays, making it difficult to achieve real-time early warning of engineering safety and failing to meet the actual needs of wind farm operation and maintenance decision-making and ecological impact assessment. Summary of the Invention

[0004] In view of this, the present invention addresses the shortcomings of the prior art by proposing an intelligent monitoring system for sediment transport in offshore wind farms, aiming to solve at least one of the problems mentioned in the background art.

[0005] This invention provides an intelligent monitoring system for sediment transport in offshore wind farms, comprising: a base module disposed on the seabed; The buoy module floats on the sea surface. The base module is electrically connected to the buoy module via a photoelectric composite cable. The bottom of the buoy module is equipped with a sensor compartment, which contains a turbidity sensor, a water depth sensor, and a high-definition camera. The sensor compartment also contains a counterweight.

[0006] In some embodiments, the base module includes: The housing has multiple connecting posts at its four bottom corners, and a base plate is fixedly connected to the bottom of each connecting post. Inside the housing, there is a battery pack and a secondary main control unit. The secondary main control unit is used for sensor data preprocessing and local power management. The detection component is located on the top of the housing.

[0007] In some embodiments, the detection components include an acoustic Doppler flow profiler, a turbidity sensor, and a high-definition camera unit.

[0008] In some embodiments, the buoy module includes: The buoy body has six independent watertight compartments inside, and the interior of each independent watertight compartment is filled with closed-cell foam material. The side walls of the buoy body are provided with multiple floats. An equipment compartment is located at the axis of the buoy body, and a control component is installed inside the equipment compartment. There are three instrument wells, and the three instrument wells are arranged in a circular array on the top of the buoy body with the equipment compartment as the center. The three instrument wells are respectively equipped with an acoustic Doppler current profiler, an optical turbidity sensor, and a camera.

[0009] In some embodiments, the control component includes: The communication module is located at the top inside the equipment compartment; The main control computing and edge processing unit is located at the bottom of the communication module. The main control computing and edge processing unit is used for real-time data analysis and intelligent decision-making. The battery pack is located at the bottom of the main control computing and edge processing unit.

[0010] In some embodiments, the top of the buoy body is also provided with a photovoltaic panel and a winch cabin.

[0011] In some embodiments, the monitoring status and sampling frequency are intelligently adjusted according to the actual changes in the concentration of suspended solids in the water body. The intelligent adjustment of the monitoring status and sampling frequency includes: In the standard monitoring mode, the sensor cabin is controlled to perform profile measurements every 2 hours, and the seabed base is photographed at regular intervals. In event-triggered mode, the profile measurement frequency is increased to once every 10-15 minutes, and the control sensor cabin is used to scan or stay at a fixed point in the water layer with the inferred high concentration of suspended matter. The decay tracking mode maintains a higher monitoring frequency than the normal mode, tracking the sedimentation process of suspended solids and the entire process of concentration returning to background levels, until it automatically switches back to the normal mode.

[0012] In some embodiments, through feature vectors Real-time analysis of sediment transport status, where C(t) is the time series of suspended matter concentration; C / t represents the rate of change in concentration; • C represents the spatial gradient of concentration; u and v represent the velocity components; u / z represents the vertical shear velocity.

[0013] In some embodiments, a clustering algorithm based on Mahalanobis distance is used for state identification, wherein the Mahalanobis distance calculation formula is: ; Where μ_i and Σ_i represent the mean vector and covariance matrix of the i-th class of states, respectively. When D_M is less than the set threshold, the system will determine that it is currently in the corresponding state. Selecting a monitoring strategy by optimizing the objective function: Where Q_data is the data quality indicator, E_efficiency is the energy efficiency indicator, T_response is the response time indicator, w is the weight of each indicator, and J represents the overall performance score of the system.

[0014] In some embodiments, the substrate has a circular cross-section, the outer diameter of the substrate is larger than the outer diameter of the connecting post, and the sidewall of the outer shell is provided with a plurality of openings.

[0015] Compared with existing technologies, the advantages of this invention are as follows: By working collaboratively with the buoy module, profile sensor compartment, and seabed base module, and interconnected via photoelectric composite cables, complete profile data from the surface to the bottom layer can be acquired synchronously, accurately tracking the entire process of sediment "suspension-transportation-settlement," thus solving the pain point of traditional seabed bases being unable to monitor the three-dimensional diffusion of sediment plumes; relying on the main control computing and edge processing unit and communication module, the "storage-recovery" mode is abandoned, enabling real-time data analysis and remote transmission, providing near-real-time early warning for the safe operation and maintenance of wind farms, highlighting the decision-making value of monitoring; through feature vector analysis and Mahalanobis distance clustering algorithms, the sediment transport status is accurately identified, and the sampling frequency is adaptively adjusted for three monitoring modes, optimizing energy efficiency while ensuring data quality, and balancing monitoring accuracy and endurance; the independent watertight compartments of the buoy module, the porous design of the seabed base, and the large-diameter substrate, combined with photovoltaic power supply and dynamic power management, enhance the system's resistance to overturning, subsidence, and marine environmental interference, meeting the needs of long-term stable monitoring.

[0016] The above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure.

[0017] Other features and aspects of this disclosure will become clearer from the following detailed description of exemplary embodiments with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 A front view of an intelligent monitoring system for sediment transport in offshore wind farms provided in an embodiment of the present invention; Figure 2 Axonometric drawing of an intelligent monitoring system for sediment transport in offshore wind farms provided in an embodiment of the present invention; Figure 3 Axonometric drawing of an intelligent monitoring system for sediment transport in offshore wind farms provided in an embodiment of the present invention; Figure 4 A flowchart of an intelligent monitoring system for sediment transport in offshore wind farms provided in an embodiment of the present invention.

[0020] The components include: 1. Photoelectric composite cable; 2. Sensor compartment; 3. Outer shell; 4. Connecting column; 5. Substrate; 6. Acoustic Doppler current profiler; 7. Turbidity sensor; 8. High-definition camera unit; 9. Buoy body; 10. Independent watertight compartment; 11. Float; 12. Equipment compartment; 13. Instrument well; 14. Photovoltaic panel; 15. Winch compartment. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0022] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0023] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0024] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0025] See Figures 1-4 As shown, an intelligent monitoring system for sediment transport in an offshore wind farm, according to an embodiment of this application, includes: The base module is located on the seabed; The buoy module floats on the sea surface. The base module is electrically connected to the buoy module via a photoelectric composite cable 1. The bottom of the buoy module is equipped with a sensor compartment 2, which contains a turbidity sensor, a water depth sensor, and a high-definition camera. The sensor compartment 2 also contains a counterweight.

[0026] It should be understood that monitoring coverage is achieved through a collaborative layout of "seabed base module + sea surface buoy module + electro-optical composite cable 1". The base module is fixed to the seabed, serving as a bottom-level monitoring node to provide near-bottom environmental data; the buoy module floats on the sea surface, undertaking the core functions of data processing, communication, and power supply. The two are connected by the electro-optical composite cable 1 to establish a stable electrical connection and data transmission channel, ensuring the coordinated operation of the seabed and sea surface equipment. The sensor compartment 2 at the bottom of the buoy module houses a turbidity sensor, a depth sensor, and a high-definition camera, which are used to capture water turbidity (indirectly reflecting suspended solids concentration), real-time depth data, and underwater visualization images, respectively. The counterweight in the sensor compartment 2 adjusts the center of gravity to ensure that the sensor compartment 2 maintains a vertical attitude in complex flow fields, avoiding measurement deviations caused by water flow disturbances.

[0027] This architecture breaks through the limitations of traditional seabed-based "bottom-sitting" single-dimensional monitoring, constructing a three-dimensional monitoring foundation encompassing the seabed, water body, and sea surface. The multi-sensor configuration of sensor compartment 2 enables the synchronous acquisition of core parameters related to sediment transport, while the counterweight design ensures the accuracy of the measurement data. The application of the photoelectric composite cable 1 simultaneously addresses the needs for power transmission and high-speed data communication, providing hardware support for subsequent real-time monitoring and intelligent decision-making, effectively compensating for the shortcomings of traditional monitoring equipment in simultaneously acquiring data from the near-bottom and upper water layers.

[0028] In some specific embodiments, the base module includes: The outer casing 3 has multiple connecting posts 4 at its four bottom corners. A base plate 5 is fixedly connected to the bottom of each connecting post 4. The inner part of the outer casing 3 is equipped with a battery pack and a secondary main control unit. The secondary main control unit is used for sensor data preprocessing and local power management. The detection component is located on the top of the housing.

[0029] It should be understood that the outer shell 3, as a protective casing, has four connecting posts 4 at its bottom corners that fix the outer shell 3 and the base plate 5 together. The circular base plate 5 increases the ground contact area to disperse the pressure of the base on the seabed, preventing excessive subsidence under soft seabed geological conditions. The battery pack inside the outer shell 3 provides continuous power to the detection components and secondary main control unit of the base module. The secondary main control unit undertakes two core tasks: first, it preprocesses the raw data collected by the detection components (such as noise reduction and format conversion) to reduce the computational burden on the buoy module's main control unit; second, it is responsible for local power management, dynamically allocating power according to the working status of the detection components to avoid energy waste. The detection components are located on the top of the outer shell 3, ensuring that the sensors can directly contact the near-bottom water and seabed surface, improving the effectiveness of data acquisition.

[0030] The combined design of the base plate 5 and connecting post 4 significantly enhances the base module's resistance to subsidence and structural stability, adapting to different seabed geological conditions. The preprocessing function of the secondary main control unit optimizes data transmission efficiency, and local power management ensures stable power supply to the base module during long-term monitoring, preventing equipment downtime due to unreasonable power distribution. The built-in battery pack, combined with the protective casing 3, effectively resists marine environmental corrosion, extends the service life of the base module, and provides a reliable guarantee for the continuous acquisition of underlying monitoring data.

[0031] In some specific embodiments, the detection components include an acoustic Doppler flow profiler 6, a turbidity sensor 7, and a high-definition camera unit 8.

[0032] It should be understood that the three types of sensors each have their own functions and complement each other. The acoustic Doppler current profiler 6 acquires the three-dimensional velocity structure and vertical profile data of the near-bottom water body through multi-beam acoustic measurement technology, and simultaneously uses acoustic backscattering signals to invert the suspended sediment concentration; the turbidity sensor 7 measures the turbidity of the near-bottom water body in real time based on the principle of optical scattering, providing a direct basis for calculating the suspended matter concentration; the high-definition camera unit 8 records the seabed sediment type (sand / mud), seabed morphology, erosion and deposition traces, and biological disturbance phenomena through scanning and shooting at preset angles, realizing the visualization of the sedimentation process. The data collected by the three types of sensors are preprocessed by the secondary main control unit and then transmitted to the buoy module through the photoelectric composite cable 1.

[0033] The combined configuration of multiple sensors enables comprehensive monitoring of the near-bottom environment, encompassing both quantitative parameters and visual imagery. The acoustic Doppler current profiler 6 provides dynamic data on flow velocity and suspended matter concentration, the turbidity sensor 7 supplements key concentration-related indicators, and the high-definition camera unit 8 provides intuitive evidence for data interpretation. This combination avoids the limitations of single-sensor monitoring. This design provides multi-dimensional, high-precision underlying data support for subsequent sediment transport state analysis, particularly for the erosion and deposition processes of the near-bottom boundary layer, achieving comprehensive capture from macroscopic dynamics to microscopic traces.

[0034] In some specific embodiments, the buoy module includes: The buoy body 9 has six independent watertight compartments 10 inside, and the interior of each independent watertight compartment 10 is filled with closed-cell foam material. The side wall of the buoy body is provided with multiple floats 11. The equipment compartment 12 is located at the axis of the buoy body 9, and the control components are installed inside the equipment compartment 12. There are three instrument wells 13, and the three instrument wells 13 are arranged in a circular array on the top of the buoy body 9 with the equipment compartment 12 as the center. The three instrument wells 13 are respectively equipped with an acoustic Doppler current profiler, an optical turbidity sensor, and a camera.

[0035] It should be understood that the buoy body 9 adopts a regular hexagonal truncated pyramid structure, with six independent watertight compartments 10 filled with closed-cell foam material. Even if a single compartment is damaged, it can still maintain positive buoyancy. The multiple floats 11 on the side walls of the buoy body 9 are symmetrically distributed, further enhancing the buoy's anti-capsulation capability. The equipment compartment 12 at the axis of the buoy body 9 serves as the core control area, providing protection and installation space for the control components. The three instrument wells 13 are arranged in a ring array around the equipment compartment 12, respectively equipped with an acoustic Doppler current profiler, an optical turbidity sensor, and a camera, to achieve the acquisition of surface water flow velocity, turbidity, and visual data. The ring layout ensures that the sensors are unobstructed and the acquisition range is more comprehensive.

[0036] The combination of independent watertight compartments 10 and closed-cell foam significantly enhances the buoy module's resistance to sinking and its survivability, adapting it to harsh marine environments. Symmetrically distributed buoys 11 optimize buoy attitude stability and reduce the impact of wind and waves on measurement accuracy. The ring array layout of the three instrument wells 13 enables the synchronous acquisition of multiple parameters of the surface water, forming a full-profile data acquisition system of "surface-water-near bottom" with the base module and sensor compartment 2. This effectively solves the problem that traditional seabed bases cannot capture sediment plume transport to the middle and upper layers, providing key hardware support for three-dimensional monitoring.

[0037] In some specific embodiments, the control component includes: The communication module is located at the top inside the equipment compartment 12; The main control computing and edge processing unit is located at the bottom of the communication module. The main control computing and edge processing unit is used for real-time data analysis and intelligent decision-making. The battery pack is located at the bottom of the main control computing and edge processing unit.

[0038] It should be understood that the communication module is located at the top of the equipment compartment 12, and uses remote communication technologies (such as satellite communication and wireless communication) to transmit the processed monitoring data to the shore-based control center in real time, while receiving shore-based commands; the main control computing and edge processing unit is located at the bottom of the communication module, serving as the system's "brain," and receives multi-source data from the base module, sensor compartment 2, and the buoy's own sensors in real time, performing real-time analysis, feature extraction, and intelligent decision-making (such as monitoring mode switching); the battery pack is located at the bottom, providing a stable power supply for the entire buoy module's equipment (communication module, main control unit, sensors, photovoltaic panel 14 and related equipment, etc.), and is linked with the intelligent power management system to achieve dynamic power distribution.

[0039] The layered architecture design ensures equipment maintainability while lowering the buoy's center of gravity, improving its stability in harsh sea conditions. The communication module enables real-time data transmission, completely eliminating the lagging "storage-recovery" mode of traditional seabed-based systems, providing near-real-time early warnings for wind farm safety operation and maintenance, and highlighting the decision-making value of monitoring. The local real-time analysis capabilities of the main control computing and edge processing units reduce data transmission latency, improve system response speed, and avoid bandwidth waste from massive raw data transmission. The large-capacity battery pack, combined with power management, ensures long-term continuous system operation, providing power support for long-term monitoring needs.

[0040] In some specific embodiments, the top of the buoy body 9 is also provided with a photovoltaic panel 14 and a winch cabin 15.

[0041] It should be understood that a photovoltaic panel 14 and a winch cabin 15 are added to the top of the buoy body 9. The photovoltaic panel 14 uses solar power generation technology to convert solar energy into electrical energy and store it in the battery pack, forming a green power supply mode of "photovoltaic power supply + battery energy storage", which dynamically replenishes power according to the intensity of sunlight. The winch cabin 15 has a built-in electric winch system (including a corrosion-resistant DC motor, a planetary gear reduction mechanism, a cable storage drum and an intelligent cable laying device). By controlling the winding and unwinding of the armored photovoltaic composite cable 1, the underwater depth of the sensor cabin 2 is adjusted to achieve profile measurement of different water layers. Moreover, the winding and unwinding of the cable is linked with the attitude control of the sensor cabin 2 to ensure the stability of the measurement process.

[0042] The addition of photovoltaic panels 14 enables the recycling of clean energy, reduces reliance on battery packs, and extends the system's endurance, making it particularly suitable for long-term offshore monitoring scenarios and reducing the frequency of maintenance and resupply. The electric winch system in the winch hull 15 provides the sensor compartment 2 with flexible depth adjustment capabilities, overcoming the limitations of fixed-depth monitoring. It allows for precise adjustment of the sensor compartment 2's position based on suspended solids concentration distribution, enabling focused monitoring of high-concentration water layers and improving the targeting and effectiveness of data acquisition. The combination of these two elements further optimizes the system's practicality and adaptability, providing power supply and motion support for the implementation of intelligent monitoring strategies.

[0043] In some specific embodiments, the monitoring status and sampling frequency are intelligently adjusted according to the actual changes in the concentration of suspended solids in the water body. This intelligent adjustment of the monitoring status and sampling frequency includes: In the standard monitoring mode, the sensor cabin is controlled to perform profile measurements every 2 hours, and the seabed base is photographed at regular intervals. In event-triggered mode, the profile measurement frequency is increased to once every 10-15 minutes, and the control sensor cabin is used to scan or stay at a fixed point in the water layer with the inferred high concentration of suspended matter. The decay tracking mode maintains a higher monitoring frequency than the normal mode, tracking the sedimentation process of suspended solids and the entire process of concentration returning to background levels, until it automatically switches back to the normal mode.

[0044] It should be understood that the system collects real-time suspended solids concentration data in the water body through sensors, automatically identifies the monitoring scenario based on the concentration change trend, and switches to the corresponding monitoring mode. In the normal monitoring mode, the system controls the sensor chamber 2 to perform profile measurements every 2 hours, and the high-definition camera unit 8 on the seabed base performs timed shooting, maintaining the background database with low-frequency acquisition to maximize energy saving; when the suspended solids concentration is detected to rise sharply or exceed the set threshold, the system switches to event-triggered mode, increasing the profile measurement frequency to once every 10-15 minutes, and at the same time, the winch chamber 15 controls the sensor chamber 2 to perform a zigzag scan or fixed-point residence in the inferred high-concentration water layer to accurately capture the core area and three-dimensional structure of the sediment plume; when the suspended solids concentration begins to decline from the peak, the system enters the decay tracking mode, maintaining a monitoring frequency higher than the normal mode, tracking the entire process of suspended solids settling and concentration recovery to the background value, and automatically switching back to the normal mode after the environment stabilizes.

[0045] This adaptive monitoring strategy breaks through the rigid limitations of traditional fixed-frequency monitoring, achieving "on-demand monitoring" while optimizing energy consumption and ensuring data integrity. The conventional mode effectively saves power and extends operating time; the event-triggered mode accurately captures key events in sediment transport (such as plume formation) through high-frequency, targeted measurements, avoiding the omission of crucial data; and the decay tracking mode fully records the final stages of sediment transport, achieving seamless monitoring of the entire "suspension-transport-sedimentation" process. The intelligent switching between these three modes enables the system to meet both long-term background monitoring needs and accurately respond to sudden sedimentation events, balancing monitoring accuracy, data integrity, and energy efficiency.

[0046] In some specific embodiments, through feature vectors Real-time analysis of sediment transport status, where C(t) is the time series of suspended matter concentration; C / t represents the rate of change in concentration; • C represents the spatial gradient of concentration; u and v represent the velocity components; u / z represents the vertical shear velocity.

[0047] It should be understood that the system extracts six core parameters from multi-source sensor data to construct a feature vector, where C(t) is the time series of suspended matter concentration (collected by turbidity sensor 7, optical turbidity sensor, etc.), reflecting the dynamic changes in concentration; C / t is the concentration change rate, characterizing how fast the concentration changes; C is the concentration spatial gradient, reflecting the spatial distribution difference of concentration; u and v are the velocity components (collected by the acoustic Doppler current profiler 6 and the acoustic Doppler current profiler in the instrument well 13), reflecting the hydrodynamic conditions. u / z represents the vertical shear of the flow velocity, which is associated with the dynamic driving factor of sediment resuspension. By calculating and analyzing this feature vector in real time, the dynamic conditions, concentration changes, and spatial distribution characteristics of sediment migration are comprehensively quantified, providing core data support for subsequent state identification.

[0048] The design of this eigenvector enables a multi-dimensional quantitative characterization of sediment transport states, overcoming the limitations of traditional single-parameter analysis (such as monitoring only concentration). Six parameters comprehensively cover the key influencing factors of sediment transport from three core dimensions: concentration, dynamics, and spatial distribution, enabling the system to accurately capture subtle changes in the transport process. The real-time analysis capability of the eigenvector provides a scientific basis for intelligent monitoring mode switching and state identification, ensuring that adjustments to monitoring strategies are based on evidence, improving the accuracy and reliability of system decision-making, and providing a quantitative analysis tool for in-depth analysis of sediment dynamics.

[0049] In some specific embodiments, a clustering algorithm based on Mahalanobis distance is used for state identification. The Mahalanobis distance calculation formula is as follows: ; Where μ_i and Σ_i represent the mean vector and covariance matrix of the i-th class of states, respectively. When D_M is less than the set threshold, the system will determine that it is currently in the corresponding state. Selecting a monitoring strategy by optimizing the objective function: Where Q_data is the data quality indicator, E_efficiency is the energy efficiency indicator, T_response is the response time indicator, w is the weight of each indicator, and J represents the overall performance score of the system.

[0050] It should be understood that, in the state identification stage, the system pre-establishes the mean vector μ_i and covariance matrix Σ_i for different sediment transport states (background state, event state, and decay state). By calculating the Mahalanobis distance D_M between the real-time feature vector X (extracted from multi-source data including sensor chamber 2, acoustic Doppler current profiler 6, and turbidity sensor 7) and various states, when D_M is less than a set threshold, the system determines that it is currently in the corresponding state. The calculation of the Mahalanobis distance eliminates interference from the correlation between parameters, improving the accuracy of state identification. In the monitoring strategy selection stage, the objective function maxJ=w1∙Q_dat is optimized. The system makes decisions based on the formula: a + w2∙E_efficiency + w3∙T_response. Here, Q_data is the data quality indicator (related to the accuracy and completeness of data collected by sensors), E_efficiency is the energy efficiency indicator (related to the power supply efficiency of photovoltaic panels, energy consumption of battery packs, etc.), T_response is the response time indicator (related to the transmission speed of communication modules, computing efficiency of main control units, etc.), and w is the weight of each indicator. By maximizing the comprehensive performance score J, the system finds the optimal balance between data quality, energy consumption, and response speed, and selects a monitoring strategy that is suitable for the current state.

[0051] Compared to traditional clustering algorithms, Mahalanobis distance clustering effectively handles the correlation between parameters, improves the accuracy of state identification, avoids misjudgments caused by parameter interference, and ensures that the system can accurately switch to the corresponding monitoring mode. The introduction of an optimized objective function makes the selection of system monitoring strategies more scientific, moving beyond a singular pursuit of data quality or energy efficiency to achieve a comprehensive optimization of all three. This ensures high-quality acquisition of key data, avoids energy waste, and guarantees a rapid response to deposition events. This solution provides core algorithmic support for the system's "intelligence," enabling the system to dynamically optimize monitoring behavior based on actual operating conditions, significantly improving overall monitoring performance.

[0052] In some specific embodiments, the transverse cross-section of the substrate 5 is circular, the outer diameter of the substrate 5 is larger than the outer diameter of the connecting post 4, and the sidewall of the outer shell 3 is provided with multiple openings.

[0053] It should be understood that the circular structure of the substrate 5, with an outer diameter larger than that of the connecting column 4, increases the contact area with the seabed, further dispersing the weight of the base module, reducing the pressure per unit area, and preventing sinking in soft seabeds. Multiple openings are provided on the sidewalls of the outer shell 3. This reduces the impact resistance of water flow on the base, mitigating the impact of wind, waves, and currents on the base's stability. It also reduces the attachment of marine organisms to the surface of the outer shell 3, preventing sensor obstruction or structural corrosion caused by biological attachment. The large diameter design of the circular substrate 5 significantly enhances the base module's resistance to subsidence, enabling it to adapt to seabeds with different geological conditions. This ensures stable base position during long-term monitoring and avoids measurement deviations caused by base subsidence. The openings on the sidewalls of the outer shell 3 effectively reduce water flow impact, improving the structural stability of the base under harsh sea conditions. Simultaneously, reducing marine organism attachment lowers the equipment maintenance frequency and extends the service life of the base module. This structural optimization improves the reliability of the base module in terms of both stability and anti-interference, providing structural assurance for the accuracy and continuity of the underlying monitoring data.

[0054] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A smart monitoring system for sediment transport in offshore wind farms, characterized in that, include: The base module is located on the seabed; The buoy module floats on the sea surface. The base module is electrically connected to the buoy module via a photoelectric composite cable. The bottom of the buoy module is equipped with a sensor compartment, which contains a turbidity sensor, a water depth sensor, and a high-definition camera. The sensor compartment also contains a counterweight.

2. The intelligent monitoring system for sediment transport in offshore wind farms according to claim 1, characterized in that, The base module includes: The housing has multiple connecting posts at its four bottom corners, and a base plate is fixedly connected to the bottom of each connecting post. Inside the housing, there is a battery pack and a secondary main control unit. The secondary main control unit is used for sensor data preprocessing and local power management. The detection component is located on the top of the housing.

3. The intelligent monitoring system for sediment transport in offshore wind farms according to claim 2, characterized in that, The detection components include an acoustic Doppler flow profiler, a turbidity sensor, and a high-definition camera unit.

4. The intelligent monitoring system for sediment transport in offshore wind farms according to claim 3, characterized in that, The buoy module includes: The buoy body has six independent watertight compartments inside, and the interior of each independent watertight compartment is filled with closed-cell foam material. The side walls of the buoy body are provided with multiple floats. An equipment compartment is located at the axis of the buoy body, and a control component is installed inside the equipment compartment. There are three instrument wells, and the three instrument wells are arranged in a circular array on the top of the buoy body with the equipment compartment as the center. The three instrument wells are respectively equipped with an acoustic Doppler current profiler, an optical turbidity sensor, and a camera.

5. The intelligent monitoring system for sediment transport in offshore wind farms according to claim 4, characterized in that, The control component includes: The communication module is located at the top inside the equipment compartment; The main control computing and edge processing unit is located at the bottom of the communication module. The main control computing and edge processing unit is used for real-time data analysis and intelligent decision-making. The battery pack is located at the bottom of the main control computing and edge processing unit.

6. The intelligent monitoring system for sediment transport in offshore wind farms according to claim 5, characterized in that, The top of the buoy is also equipped with photovoltaic panels and a winch cabin.

7. The intelligent monitoring system for sediment transport in offshore wind farms according to claim 6, characterized in that, The monitoring status and sampling frequency are intelligently adjusted based on the actual changes in the concentration of suspended solids in the water body. This intelligent adjustment of the monitoring status and sampling frequency includes: In the standard monitoring mode, the sensor cabin is controlled to perform profile measurements every 2 hours, and the seabed base is photographed at regular intervals. In event-triggered mode, the profile measurement frequency is increased to once every 10-15 minutes, and the control sensor cabin is used to scan or stay at a fixed point in the water layer with the inferred high concentration of suspended matter. The decay tracking mode maintains a higher monitoring frequency than the normal mode, tracking the sedimentation process of suspended solids and the entire process of concentration returning to background levels, until it automatically switches back to the normal mode.

8. The intelligent monitoring system for sediment transport in offshore wind farms according to claim 7, characterized in that, Through feature vectors Real-time analysis of sediment transport status, where C(t) is the time series of suspended matter concentration; C / t represents the rate of change in concentration; • C represents the spatial gradient of concentration; u and v represent the velocity components; u / z represents the vertical shear velocity.

9. The intelligent monitoring system for sediment transport in offshore wind farms according to claim 8, characterized in that, State identification is performed using a clustering algorithm based on Mahalanobis distance. The Mahalanobis distance calculation formula is as follows: ; Where μ_i and Σ_i represent the mean vector and covariance matrix of the i-th class of states, respectively. When D_M is less than the set threshold, the system will determine that it is currently in the corresponding state. Selecting a monitoring strategy by optimizing the objective function: Where Q_data is the data quality indicator, E_efficiency is the energy efficiency indicator, T_response is the response time indicator, w is the weight of each indicator, and J represents the overall performance score of the system.

10. The intelligent monitoring system for sediment transport in offshore wind farms according to claim 9, characterized in that, The substrate has a circular cross-section, and the outer diameter of the substrate is larger than the outer diameter of the connecting post. The sidewall of the outer shell is provided with multiple openings.

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