A scour pit shape monitoring system and method for offshore wind power pile foundation

Abstract

The application discloses a kind of offshore wind power pile foundation scour pit form monitoring system and monitoring method, comprising: the light sensor array of being arranged along pile foundation circumference, the sonar scanning module being positioned in the side of meeting flow, and with the light sensor array and sonar scanning module communication connection data processing module;Light sensor array and the sonar scanning module of meeting flow side combination of 360 ° annular distribution along pile foundation circumference multi-source perception architecture, wherein light ray sensor covers 1-2 times design scour depth below original seabed surface to 2m of scour sensitive area above seabed surface, narrow-spectrum red light sensor focuses 0.5m-3m of accumulation partition above seabed surface, and corresponding sensor group is activated by partition unit dynamically dividing scour area and accumulation area.Light ray sensor is used to collect scour area exposure timing data and red light reflection data in accumulation area, while combining the section data of the side of meeting flow scanned by sonar, to realize complete coverage to the scour pit form around pile foundation from spatial dimension.

Description

Technical Field

[0001] This invention relates to the field of offshore wind power technology, and in particular to a monitoring system and method for monitoring the morphology of scour pits in offshore wind turbine foundations. Background Technology

[0002] The combined dynamic forces of waves and tides in nearshore areas have a significant impact on marine engineering structures, with the localized scour problem faced by offshore wind turbine foundations being particularly prominent during their service life. Under the combined action of waves and tides, the seabed soil surrounding the foundation is prone to three-dimensional asymmetric scour patterns, directly affecting the stability of the foundation structure and the safe operation of the power generation facilities.

[0003] When a pile foundation is in a stable unidirectional ocean current environment (such as tidal currents or coastal currents), the water flow impacts the pile foundation in a constant direction, forming a horseshoe vortex system on the upstream side. This vortex structure draws down the bottom sand in front of the pile, forming a local scour pit. After the water flows around the pile foundation, a wake vortex zone is generated on the downstream side. Here, the flow velocity decreases, leading to a reduction in sediment transport capacity. The scoured sand is deposited in the wake vortex zone, forming fan-shaped or teardrop-shaped deposits. This asymmetric scour morphology involves complex variations in pit bottom depth gradients and three-dimensional deposit characteristics.

[0004] For this type of asymmetric scour, existing light detection or sonar technologies cannot accurately obtain the depth gradient at the bottom of the pit and the three-dimensional shape of the accumulation.

[0005] Therefore, it is necessary to provide a monitoring system and method for monitoring the erosion pit morphology of offshore wind turbine foundations in order to solve the above-mentioned technical problems. Summary of the Invention

[0006] This invention overcomes the shortcomings of the prior art and provides a monitoring system and method for monitoring the morphology of scour pits in offshore wind turbine foundations.

[0007] To achieve the above objectives, the technical solution adopted by this invention is: a monitoring system for the morphology of scour pits in offshore wind turbine foundations, comprising:

[0008] An optical sensor array is disposed on the outer periphery of the pile foundation. The optical sensor array includes: a light light sensor and a narrow-spectrum red light sensor that are selected and activated according to the division of scour zones and deposition zones; wherein, the light light sensor is used to acquire the bottom slope data of the scour zone, and the narrow-spectrum red light sensor is used to acquire the red light reflection intensity data of the deposition zone.

[0009] The sonar scanning module is used to emit horizontal sound waves to acquire continuous cross-sectional data of the scour zone; and

[0010] The data processing module is communicatively connected to the optical sensor array and the sonar scanning module. It is used to fuse the slope data of the pit bottom, the red light reflection intensity data and the continuous cross-sectional data to generate the three-dimensional morphology of the scour pit and the accumulation body around the pile foundation.

[0011] In a preferred embodiment of the present invention, the adjacent spacing of the light sensors along the axial direction of the pile foundation is 3cm-10cm, the circumferential spacing is 10°-15°, and the lens is set to a horizontal orientation.

[0012] In a preferred embodiment of the present invention, the narrow-spectrum red light sensor is arranged at 15°-20° intervals along the circumference of the pile foundation, with the lens axis forming a downward tilt angle of 30°-45° with the normal to the pile foundation surface, and the detection range covering the outer wall of the pile foundation to the edge of the accumulation zone with a radius of 1-2 times the pile diameter.

[0013] In a preferred embodiment of the present invention, the method for dividing a scour zone into a sludge zone and a sludge zone includes the following steps:

[0014] Short-term activation of all light sensors to collect and filter light intensity data;

[0015] Calculate the average light intensity and fluctuation coefficient of each light sensor;

[0016] The fan-shaped area is divided along the circumference according to the zoning rules. The proportion of light sensors that meet the light intensity standard is counted. The K-means clustering algorithm is used to generate the boundary angle between the scour zone and the accumulation zone.

[0017] The zoning rules are as follows: for the scouring zone, the sensor light intensity is ≥50 lux and the fluctuation coefficient is ≤5%; for the stacking zone, the sensor light intensity is ≤10 lux and the fluctuation coefficient is ≤3%.

[0018] In a preferred embodiment of the present invention, the data processing module includes a slope calculation unit;

[0019] The slope calculation unit calculates the slope of the scour pit bottom based on the exposure time series data of the light sensor: sensor data from the same circumferential profile are selected and arranged in ascending order of exposure time; the vertical height difference and time difference between adjacent sensors are calculated, and the slope is solved by combining the water erosion advance rate.

[0020] In a preferred embodiment of the present invention, the data processing module further includes a stacking thickness calculation unit;

[0021] The sediment deposition thickness calculation unit calculates the sediment deposition thickness based on the Lambert-Beer law:

[0022] The narrow-spectrum red light sensor emits a light beam with a wavelength of 630±10nm and receives the light intensity I reflected by accumulated sediment.

[0023] According to the formula Calculate the thickness d, where The initial reference light intensity is given by k, where k is the local red light absorption coefficient of the sediment. The reflectivity of the mud and sand surface. This refers to the light transmittance of the water body.

[0024] In a preferred embodiment of the present invention, the data processing module further includes a fusion unit;

[0025] The fusion unit unifies the pit bottom slope data, red light reflection intensity data and continuous cross-sectional data into the local coordinate system of the pile foundation through spatiotemporal registration. It uses the iterative nearest point algorithm to register the sonar point cloud and the slope data of the light sensor, and generates the three-dimensional shape of the accumulation body through inverse distance weighted interpolation. It then stitches the data into a full-circumferential asymmetric morphological model that includes the scour pit depth gradient and the accumulation body thickness distribution.

[0026] A method for monitoring the morphology of scour pits in offshore wind turbine foundations includes the following steps:

[0027] S1. An array of optical sensors is arranged along the circumference of the pile foundation, and a sonar scanning module is set on the flow-facing side. The scour zone and the accumulation zone are divided by the partition unit.

[0028] S2. Activate the light sensor in the scour zone to obtain exposure time data, and solve the slope of the scour pit bottom through the slope calculation unit;

[0029] S3. Activate the narrow-spectrum red light sensor of the sedimentation zone and calculate the thickness of sediment deposition based on the Lambert-Beer law;

[0030] S4. The sonar scanning module acquires the cross-sectional data of the upstream side, and the fusion unit fuses the three types of data to generate a three-dimensional scour morphology model.

[0031] In a preferred embodiment of the present invention, in step S2, the exposure timing data of the light sensor records the time stamp of the sudden increase in light intensity through the clock synchronization unit, associates it with preset three-dimensional coordinate parameters, and forms a scour depth timing signal chain according to the exposure order from high to low height.

[0032] In a preferred embodiment of the present invention, step S4, data fusion includes:

[0033] Sonar point cloud data is converted into three-dimensional rectangular coordinates, and invalid data is removed by wavelet thresholding.

[0034] The elevation of sonar point clouds is corrected using slope data from light sensors, and the bottom morphology of the uncovered areas is extrapolated.

[0035] Spatial interpolation of the accumulation thickness data, combined with the accumulation partition boundaries extrapolated by sonar, generates a three-dimensional model of the fan-shaped accumulation body.

[0036] This invention addresses the shortcomings of the prior art and has the following beneficial effects:

[0037] This invention provides a monitoring system for the morphology of scour pits in offshore wind turbine foundations. It employs a multi-source sensing architecture combining a circumferentially distributed array of optical sensors and a sonar scanning module on the upstream side. The optical sensors cover the scour-sensitive area, while narrow-spectrum red light sensors focus on the deposition zone. By dynamically dividing the scour and deposition zones and activating corresponding sensor groups, the monitoring system can selectively collect temporal data on scour zone exposure and red light reflectance data on deposition zones. Simultaneously, by combining this with cross-sectional data of the scour zones obtained from sonar scanning, it achieves complete coverage of the circumferential asymmetric morphology of the scour pits and deposition bodies surrounding the foundation. Compared to existing technologies, this invention overcomes the blind spots in monitoring complex scour morphologies and improves the spatial resolution and completeness of underwater topographic data.

[0038] The data processing module of this invention automatically divides scour zones and deposition zones through clustering algorithms and light intensity threshold analysis. It infers the slope of the scour pit bottom based on the exposure time-series signal chain from the light sensor, and uses an iterative nearest-point algorithm and inverse distance weighted interpolation to complete the spatiotemporal registration and 3D reconstruction of multi-source data. This transforms local measurement data into regional features. By combining a real-time dynamic fusion algorithm, it deeply couples the high-frequency temporal characteristics of the light sensor, the spatial morphological details of the sonar, and the thickness quantification data from the red light sensor, generating a 3D visualization model that includes the scour pit depth gradient, the deposition thickness distribution, and the equilibrium coefficient.

[0039] This invention addresses the technical challenge of increased sonar measurement errors caused by the low density and high porosity of sediment deposits on the back-flow side. It employs a narrow-spectrum red light sensor to emit a 630±10nm wavelength beam, calculates the sediment deposit thickness based on the Lambert-Beer law, and combines this with local sediment red light absorption coefficient calibration to achieve high-precision measurement of loose sediment thickness. Existing technologies suffer from high ranging errors in the sediment region due to sound wave energy attenuation. This invention, however, avoids interference from acoustic impedance differences through optical reflection, directly improving the reliability of back-flow side data. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a block diagram of a monitoring system according to a preferred embodiment of the present invention;

[0042] Figure 2 This is a schematic diagram of a light sensor array according to a preferred embodiment of the present invention;

[0043] Figure 3 This is a flowchart of the monitoring method according to a preferred embodiment of the present invention;

[0044] In the diagram: 100, pile foundation; 200, light sensor; 300, narrow-spectrum red light sensor; 400, data processing module. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein. Therefore, the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0047] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used 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 limiting the scope of protection of this application.

[0048] 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 fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this application based on the specific circumstances.

[0049] The seabed in nearshore areas is mostly composed of loose, unconsolidated sedimentary soils such as silt, fine sand, or fine sand. These unique geological conditions make the seabed around pile foundations susceptible to erosion by waves and currents. Erosion not only weakens the bearing capacity of the surrounding soil but can also lead to pile foundation exposure, tilting, or even instability, seriously threatening the long-term safety of nearshore engineering facilities. Various underwater pile foundation erosion monitoring technologies exist, with commonly used technologies including sonar and fiber Bragg grating sensors.

[0050] Sonar technology measures the shape and depth of seabed scour pits around pile foundations by emitting sound waves and receiving their reflected waves. When sound waves encounter interfaces between media of different densities (such as the boundary between water and seabed), they are reflected. By measuring the return time and intensity of the sound waves, detailed information about the seabed can be obtained. However, the resolution of sonar is limited by the wavelength of the sound waves. In complex marine environments, multipath propagation can lead to data distortion, and loose sediment in depositional areas can absorb sound signals, reducing sonar resolution.

[0051] Fiber Bragg grating sensors utilize the propagation characteristics of light in optical fibers to obtain strain or temperature information along the fiber by measuring the wavelength change of the light reflected from the Bragg grating. This technology is highly sensitive and resistant to electromagnetic interference, but it can only detect the exposed state of the pile foundation surface and cannot capture the depth gradient at the bottom of the pit or the three-dimensional morphology of the accumulated mass.

[0052] Therefore, to address the problem of monitoring asymmetric scour patterns, this invention provides a scour pit morphology monitoring system for offshore wind turbine foundations. It employs a multi-source sensing architecture combining a light sensor array distributed along the circumference of the pile foundation with a sonar scanning module on the upstream side. The light sensor covers the scour-sensitive area, while the narrow-spectrum red light sensor focuses on the accumulation zone. By dynamically dividing the scour zone and accumulation zone and activating the corresponding sensor groups, the monitoring system can selectively collect exposure time-series data of the scour zone and red light reflection data of the accumulation zone. Simultaneously, by combining the cross-sectional data of the scour zone obtained from sonar scanning, it achieves complete circumferential coverage of the asymmetric morphology of the scour pit and accumulation body around the pile foundation.

[0053] Example 1:

[0054] Figure 1 A block diagram of a monitoring system for scour pit morphology of offshore wind turbine pile foundations according to this embodiment is shown. The monitoring system includes: an array of optical sensors arranged along the circumference of the pile foundation, a sonar scanning module, and a data processing module communicatively connected to the optical sensor array and the sonar scanning module.

[0055] The pile foundation is a single pile foundation for offshore wind power, which is divided into two parts along its length. One part is located above the sea level and connects to the wind turbine, while the other part is located below the sea level and its lower end is buried in the seabed.

[0056] like Figure 2As shown, the optical sensor array consists of two types of sensors, distributed in a 360° ring around the outer wall of the pile foundation. Specifically, it includes a light sensor and a narrow-spectrum red light sensor. The light sensor extends along the pile foundation axis from 1.5 times the designed scour depth below the original seabed surface to 2m above the seabed surface. The axial spacing between adjacent light sensors is 3cm-10cm, and the circumferential spacing is 10°-15°, with a horizontal orientation, forming a three-dimensional monitoring network covering the potential scour range. The narrow-spectrum red light sensor is only distributed within a height range of 0.5m-3m above the seabed surface, with one sensor placed every 15°-20° along the circumference of the pile foundation. The lens axis forms a downward tilt angle of 30°-45° with the normal to the pile foundation surface, ensuring that the detection range covers the outer wall of the pile foundation to the edge of the accumulation zone (within a radius of 1-2 times the pile diameter).

[0057] The data processing module is communicatively connected to the optical sensor array and the sonar scanning module. This data processing module includes: a clock synchronization unit, a partitioning unit, a slope calculation unit, a build-up thickness calculation unit, and a fusion unit.

[0058] In this embodiment, the clock synchronization unit records the timestamp of a sudden increase in light intensity for each light sensor in real time and associates it with its preset three-dimensional coordinate parameters:

[0059] Vertical position: The height of the light sensor above the original seabed surface (H1, H2…H) n (unit: cm), stored in the module's built-in database after calibration;

[0060] Circumferential position: Angular coordinates (θ1, θ2…θ) of the light sensor within the arc segment on the front side of the airflow. n (unit: °), used to distinguish the differences in scouring rates in different circumferential regions.

[0061] For example, the light sensor numbered S1 is located at a height of H1=50cm and a circumferential angle of θ1=0° (directly facing the flow), and its exposure time is recorded as t1; the light sensor numbered S2 is located at H2=40cm and an angle of θ2=10°, and its exposure time is recorded as t2; when H1>H2 and t1<t2, it can be determined that the scour pit develops vertically downward in the circumferential region.

[0062] The partitioning unit in this embodiment is used to briefly activate all light sensors, calculate and divide the upstream and downstream regions (scouring and deposition zones) based on the feedback light intensity information and location. The specific partitioning method includes the following steps:

[0063] Step A1: Activate all light sensors for 1-2 minutes, setting the sampling frequency to 1Hz. During the first 10 seconds of activation, the light sensors collect the initial ambient light intensity as a baseline value (I0), where:

[0064] Due to sediment cover, the baseline value of the light sensor below the seabed is ≤5 lux;

[0065] The light sensor above the seabed is exposed to seawater, with a baseline value I0 ≥ 50 lux (the specific value is determined by seawater transparency, depth and lighting conditions, and is calibrated through a water tank test before leaving the factory).

[0066] Step A2: During the activation period, all light sensors synchronously upload light intensity data (I ij , where i is the sensor number and j is the sampling time), and the raw data is filtered (using the 5-point moving average method to eliminate instantaneous interference) and outlier removal (removing data points that deviate from the mean by 3 times the standard deviation).

[0067] Step A3: Calculate the average light intensity value for each light sensor. and light intensity fluctuation coefficient ( ),in:

[0068] The scour zone sensor is exposed to seawater, and the light intensity is stable (CV). i ≤5%) and ≥50 lux;

[0069] The light intensity of the sediment-covered zone sensor is low due to sediment accumulation. ≤10 lux) and small fluctuations (CV) i ≤3%)

[0070] Transition zone sensors (partial coverage or water flow disturbance) experience large light intensity fluctuations (CV). i >8%).

[0071] Step A4: Divide the pile foundation circumference into multiple sector-shaped areas at intervals of 10-30°;

[0072] Calculate the average light intensity in each region The percentage of light sensors with a value of ≥50 lux is P1. If P1 ≥ 70%, and these light sensors are continuously distributed along the height direction (sensors with a vertical spacing ≤ 10 cm all meet this condition). If the value is ≥50 lux, the fan-shaped area is determined to be a scour zone.

[0073] Calculate the average light intensity within each sector region. The percentage of light sensors with a light intensity of ≤10 lux is P2. If P2 ≥ 60%, and the light sensors are highly concentrated in the 0-1m range above the seabed (i.e., the original exposed area becomes a low light intensity state), then the fan-shaped area is determined to be an accumulation area.

[0074] Step A5: Use a clustering algorithm (K-means clustering, K=2) to analyze the circumferential angle θ and average light intensity of all light sensors. Two-dimensional clustering is performed, automatically generating the boundary angles θ1 and θ2 between the scour zone and the accumulation zone. For example, in the clustering results, θ1 = 30°-150° represents the scour zone, θ2 = 210°-330° represents the accumulation zone, and the rest are transition zones.

[0075] Based on the partitioning results, the optical sensor array activates some sensors as front-flow side sensor groups and back-flow side sensor groups respectively.

[0076] Among them, the upstream sensor group only activates the light sensors in the fan-shaped area of ​​the scour zone (the other light sensors are in a dormant state), and the coverage height ranges from 1.5 times the design scour depth below the original seabed to 2m above the seabed.

[0077] Initially, multiple light sensors in the upstream sensor group are completely covered by seabed sediment, placing them in a low-light / no-light environment below the seabed surface. At this time, the light is weak or completely absent, and the light sensors output low-intensity signals or no light-intensity signals. When scouring occurs around the pile foundation, the water flow carries away the sediment around the light sensors, gradually exposing them to seawater. The natural light (or transmitted light from the water) in the seawater environment is significantly stronger than that under sediment cover, causing the light intensity detected by the light sensors to suddenly increase (sudden increase in light intensity). The data processing module determines that the light sensor at this location has been exposed by recognizing this signal change.

[0078] It should be noted that the upstream arc segment refers to the angle of the fan-shaped area radiating from the scour pit around the pile foundation axis, such as 150°, 180° or 220°. Correspondingly, after removing the upstream arc segment from the pile foundation circumference, what remains is the downstream arc segment.

[0079] Furthermore, the sensor array on the upstream side is linearly distributed along the arc segment of the pile foundation on the upstream side. In the initial stage of scouring, seabed sediment covers all sensors. As the water flow continues to erode the seabed on the upstream side, the scouring pit gradually extends from the seabed surface to a deeper depth. Due to the vertical gradient of water flow velocity (the velocity near the water surface is higher than the velocity near the bottom of the pit), the sediment around the higher sensors (closer to sea level) is first carried away by the shear force of the water flow, causing the sensors at that location to be exposed first. Subsequently, as the depth of the scouring pit increases, the lower sensors (closer to the original seabed surface) lose their sediment cover in turn. In this process, the exposure order of the sensors strictly follows the rule of "from high to low height", forming a time-series signal chain directly related to the development depth of the scouring pit.

[0080] The slope calculation unit in this embodiment calculates the slope of the scour pit bottom based on exposure time-series data and location parameters. The specific calculation method for the scour pit bottom slope includes the following steps:

[0081] Step B1: Select light sensor data from the same circumferential profile (e.g., within the range of θ=0°±5°) to eliminate interference from circumferential scouring inhomogeneity.

[0082] Step B2: Arrange the selected light sensors in ascending order of exposure time to obtain the sequence [(t1, H1), (t2, H2), ..., (t...]. k H k )], where t1 < t2 < ... < t k And H1 > H2 > ... > H k .

[0083] Step B3: For adjacent light sensors i and i+1, the vertical height difference ΔH = H i -H i+1 Time difference Δt = t i+1 -t i Assume that the bottom of the erosion pit is approximately a linear slope in a short period of time, and the erosion advance velocity of the water flow along the bottom of the pit is v = ΔL / Δt (where ΔL is the horizontal erosion distance). Then the slope α satisfies: ;

[0084] The water flow velocity v is obtained through real-time hydrological sensor data, and the value of α can be solved by substituting the data into the sensor.

[0085] Step B4: After calculating the slope of multiple sets of adjacent light sensor data for the same circumferential profile, the weighted average method is used to eliminate random errors, and finally the slope value of the pit bottom of the profile is output.

[0086] Through the coordinated processing of the upstream sensor group, clock synchronization unit, and slope calculation unit, the system can capture the dynamic development process of the scour pit in real time. When the depth of the scour pit exceeds the design threshold (e.g., 50cm) or the slope is greater than 1:3 (vertical: horizontal), the data processing module automatically triggers an early warning signal, providing a quantitative basis for the safety assessment of the pile foundation structure. At the same time, this reverse calculation algorithm complements the cross-sectional data from the sonar scanning module—the light sensor provides high-frequency temporal characteristics, and the sonar provides spatial morphological details. The fusion of the two enables high-precision reconstruction of the three-dimensional morphology of the scour pit.

[0087] The back-current side sensor group activates only the narrow-spectrum red light sensor within the fan-shaped area of ​​the sediment deposition zone, monitoring the 0-1m height range above the seabed surface. It emits narrow-spectrum red light with a wavelength of 630±10nm to acquire the red light reflection intensity data of the deposited sediment. After the narrow-spectrum red light penetrates the water, some of the light is scattered / absorbed by the sediment particles, and the remaining light is reflected back to the receiving module of the narrow-spectrum red light sensor after reflection from the sediment surface. The relationship between the reflected light intensity and the deposition thickness follows the Lambert-Beer law: ;

[0088] Where I represents the measured reflected light intensity of the receiving module;

[0089] I0 is the initial reference reflected light intensity, that is, the reflected light intensity without accumulation;

[0090] k is the red light absorption coefficient of local sediment (unit: m). -1 The red light absorption coefficient k is positively correlated with the particle size and porosity of sediment. Local seabed sediment samples were collected, and the red light absorption coefficient k was measured in the laboratory.

[0091] d is the packing thickness (unit: m);

[0092] R(θ) is the surface reflectance of mud and sand (related to the incident angle θ; when θ=35°, the measured R≈0.25±0.05).

[0093] T w This represents the light transmittance of the water body (single transmission, negatively correlated with turbidity, on-site calibration value).

[0094] In this embodiment, the method for monitoring the sediment deposition morphology on the back-flow side using a back-flow side sensor array includes the following steps:

[0095] Step C1: After system installation, in the absence of sediment accumulation, the backflow side sensor group (multiple narrow-spectrum red light sensors in the fan-shaped area of ​​the sediment accumulation zone) continuously samples the reflected light intensity 100 times (sampling interval 1s), removes the maximum and minimum values, and takes the average value as I0; simultaneously records environmental parameters, including water temperature, salinity, turbidity, etc., and stores them in the benchmark parameter library of the data processing module as a subsequent comparison benchmark.

[0096] Step C2: Apply Kalman filtering to the reflected light intensity data from step C1 to eliminate instantaneous light intensity fluctuations caused by wave disturbances, and set a reflected light intensity threshold range [0.1I0, 1.2I0]. Data outside the range is marked as abnormal (such as biological attachments obstructing the lens), and the sliding average value of the previous 5 minutes is automatically used as a replacement.

[0097] Step C3: After sediment deposition occurs, the intensity I of the reflected light received by the sensor decreases exponentially with the increase of sediment thickness. Based on the Lambert-Beer law, the sediment deposition thickness is calculated. , among which, T w Turbidity data is acquired in real time using synchronously deployed turbidity sensors and substituted into empirical formulas. .

[0098] Step C4: Combine multi-sensor spatial coordinates with interpolation algorithms to obtain the three-dimensional shape of the stack.

[0099] In this embodiment, the sonar scanning module is located on the upstream side and is used to emit horizontal sound waves to acquire continuous cross-sectional data. The sonar scanning module adopts a high-frequency mechanical scanning side-scan sonar (preferably Teledyne BlueView BV5000) and mainly consists of the following components:

[0100] Transducer array: Composed of 128 piezoelectric ceramic elements, operating frequency 400kHz–600kHz (adjustable), beamwidth 0.5° horizontal × 20° vertical, ensuring angular resolution ≤0.5° in the horizontal direction, and can distinguish targets with a spacing of 0.1m;

[0101] Mechanical scanning unit: Drives the transducer to perform a 180° reciprocating rotational scan along the circumference of the pile foundation (the scanning range covers the fan-shaped area of ​​θ=30°-150° on the upstream side of the scour zone), with a scanning speed of 5° / s and a scanning cycle of 36s per revolution;

[0102] Data acquisition unit: Built-in 24-bit A / D converter, sampling rate 1MHz, range 0.5m–50m (distance from pile foundation surface), ranging accuracy ±1% (full range).

[0103] The module is installed at a height of 1.5m above the seabed surface on the upstream side of the pile foundation. The transducer axis is tilted downward by 10°±2° to the horizontal direction to ensure that the acoustic beam covers a range from 1.5 times the design scour depth below the original seabed surface to 0.5m above the seabed surface, completely overlapping with the monitoring area of ​​the upstream light sensor.

[0104] The method for acquiring sonar scanning data includes the following steps:

[0105] Step D1: Linked with the scour zone determination results of the partition unit, the scan is started only after the partition unit outputs the "scour zone boundary stable" signal (θ1 and θ2 fluctuations ≤ 5° in 3 consecutive partition results) to avoid invalid data collection caused by water flow disturbance in the transition zone.

[0106] Each scan generates a three-dimensional data point set of radial distance-angle-echo intensity within a 180° sector area, in the format (r,θ,A), where: r is the radial distance of the target point from the sonar transducer, in meters; θ is the scanning angle; and A is the echo intensity, reflecting the target's reflection characteristics. For scouring the hard soil layer at the bottom of the pit, A ≥ -20 dB, and for loose mud and sand, A ≤ -40 dB, in dB.

[0107] Step D2: Convert the polar coordinates (r, θ) to three-dimensional rectangular coordinates (X, Y, Z) in the local coordinate system of the pile foundation, where, The origin of the Z-axis is the original seabed surface, and downward is the positive direction.

[0108] Furthermore, noise filtering and invalid data removal were performed on the sonar scan data. Noise filtering specifically involved wavelet threshold denoising (using a db4 wavelet basis, 3 decomposition layers, and hard thresholding) to eliminate echo noise generated by bubbles, marine organisms, etc. Invalid data removal involved setting an echo intensity threshold A ≥ −35dB; data below this value was determined to be reflections from water bodies or loose suspended sediment and was not included in the reconstruction of the scour pit morphology.

[0109] The reason why sonar scanning is not used on the backflow side in this embodiment is that the sediment deposits on the backflow side have low density and high porosity, which leads to increased sonar error. Sonar relies on sound wave reflection to measure distance, but the high porosity of the loose deposits causes sound wave energy attenuation. The higher the porosity, the higher the sound wave attenuation.

[0110] The fusion unit of this embodiment fuses exposure time-series data, red light reflectance intensity data, and continuous cross-sectional data to form a three-dimensional morphology of a scour pit, including the following steps:

[0111] Step E1: The exposure timestamp (t) of the light sensor, the sonar scanning angle (θ), and the coordinates (H, θ) of the narrow-spectrum red light sensor are uniformly transformed to the local coordinate system of the pile foundation (with the pile foundation axis as the Z-axis and the original seabed surface as the X and Y planes) through the clock synchronization unit, so as to achieve the benchmark normalization of the time and space dimensions.

[0112] Step E2: Based on the point cloud data (X,Y,Z) of the scour zone obtained by sonar scanning, construct an initial three-dimensional grid with a resolution of 0.1m×0.1m, and correct the grid node elevation values ​​using the pit bottom slope data α calculated by the light sensor. This is used to fill in the morphological data of areas not covered by sonar (such as local depressions at the bottom of the pit), and generate a three-dimensional model of the scour pit on the upstream side that includes parameters such as the bottom elevation, slope, and scour range.

[0113] Step E3: Spatial interpolation processing is performed on the accumulation thickness data collected by the narrow-spectrum red light sensor on the backflow side. Combined with the accumulation partition boundary, a three-dimensional model of the fan-shaped accumulation body is constructed. The model parameters include the accumulation thickness distribution, total volume, and vertex spatial coordinates.

[0114] Step E4: Align and topologically fuse the scour pit model from Step E2 with the accumulation model from Step E3 to form an asymmetric scour morphology model covering the 360° circumference of the pile foundation. The model is output in STL format and can be directly imported into finite element analysis software for structural stability calculation. It automatically extracts key indicators such as the maximum depth of the scour pit, average slope, accumulation volume, and scour-accumulation balance coefficient (scour volume / accumulation volume). When any indicator exceeds the preset safety threshold, a real-time early warning mechanism is triggered.

[0115] Through the above-mentioned technical means, the present invention achieves deep coupling of multi-source heterogeneous data and high-precision reconstruction of the full circumferential morphology, effectively solving the problems of data fragmentation and coverage blind spots in traditional monitoring technologies.

[0116] Existing technologies mostly focus on monitoring scour pits on the upstream side, neglecting the impact of deposits on the stress balance of the pile foundation. The full-circumference model dynamically divides scour and deposit zones, and combines upstream sonar and downstream narrow-spectrum red light sensor data to achieve complete capture of the asymmetric morphology of "scour pit-deposit" within a 360° circle around the pile foundation, especially solving the problem of monitoring loose deposits on the downstream side.

[0117] It is worth noting that all sensors in the optical sensor array, including the light sensor and the narrow-spectrum red light sensor, are equipped with waterproof transparent protective covers.

[0118] Example 2:

[0119] Figure 3 A flowchart of the scour pit morphology monitoring method of this embodiment is shown. The monitoring method includes the following steps: Step S1, deploying an array of optical sensors along the circumference of the pile foundation, setting up a sonar scanning module on the upstream side, and dividing the scour zone and the deposition zone by a partitioning unit; Step S2, activating the optical sensors of the scour zone to acquire exposure time-series data, and solving the slope of the scour pit bottom by a slope calculation unit; Step S3, activating the narrow-spectrum red light sensor of the deposition zone, and calculating the sediment deposition thickness based on the Lambert-Beer law; Step S4, the sonar scanning module acquires cross-sectional data on the upstream side, and the fusion unit fuses the three types of data to generate a three-dimensional scour morphology model.

[0120] In step S2, the exposure timing data of the light sensor is recorded by the clock synchronization unit as a time stamp of the sudden increase in light intensity, and associated with preset three-dimensional coordinate parameters to form a scour depth timing signal chain in the exposure order from high to low.

[0121] In step S4, data fusion includes:

[0122] Step S41: Convert the sonar point cloud data into three-dimensional rectangular coordinates, and remove invalid data by wavelet thresholding;

[0123] Step S42: Use the slope data from the light sensor to correct the elevation of the sonar point cloud and extrapolate the bottom morphology of the uncovered area;

[0124] Step S43: Spatial interpolation is performed on the accumulation thickness data, and the accumulation partition boundary is combined with sonar extrapolation to generate a three-dimensional model of the fan-shaped accumulation body.

[0125] This embodiment dynamically divides the scour zone and the deposition zone, selectively activates the light sensor in the scour zone to obtain exposure time series data to solve the bottom slope of the pit, and uses the narrow-spectrum red light sensor in the deposition zone to calculate the thickness of sediment deposition based on the Lambert-Beer law. It also combines the data from the upstream cross section of the sonar scan for multi-source fusion, enabling the monitoring process to accurately capture the full circumferential asymmetric morphology of the "scour-deposition" around the pile foundation.

[0126] Furthermore, by coupling the high-frequency timing characteristics of the light sensor, the spatial morphological details of the sonar, and the thickness quantification data of the red light sensor, the monitoring limitations of traditional single technology are broken through, and the synchronous acquisition of the depth gradient of the scour pit and the thickness distribution of the deposit is directly realized.

[0127] A three-dimensional visualization model containing key parameters such as scour pit slope and accumulation volume was provided for the structural stability assessment of offshore wind turbine pile foundations, providing a scientific basis for the formulation of engineering safety early warning and protection measures.

[0128] Those skilled in the art will understand that other details of the liquefaction discrimination device according to embodiments of the present invention are the same as the corresponding details described in the liquefaction discrimination method according to embodiments of the present invention, and will not be repeated here to avoid redundancy.

[0129] Based on the preferred embodiments of the present invention described above, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A monitoring system for the morphology of scour pits in offshore wind turbine foundations, characterized in that, include: An optical sensor array is disposed on the outer periphery of the pile foundation. The optical sensor array includes: a light light sensor and a narrow-spectrum red light sensor that are selected and activated according to the division of scour zones and deposition zones; wherein, the light light sensor is used to acquire the bottom slope data of the scour zone, and the narrow-spectrum red light sensor is used to acquire the red light reflection intensity data of the deposition zone. The sonar scanning module is used to emit horizontal sound waves to acquire continuous cross-sectional data of the scour zone; and The data processing module is communicatively connected to the optical sensor array and the sonar scanning module. It is used to fuse the pit bottom slope data, red light reflection intensity data and continuous cross-sectional data to generate the three-dimensional morphology of the scour pit and accumulation body around the pile foundation. The method for dividing the flush partition and the accumulation partition includes the following steps: Short-term activation of all light sensors to collect and filter light intensity data; Calculate the average light intensity and fluctuation coefficient of each light sensor; The fan-shaped area is divided along the circumference according to the zoning rules. The proportion of light sensors that meet the light intensity standard is counted. The K-means clustering algorithm is used to generate the boundary angle between the scour zone and the accumulation zone. The zoning rules are as follows: for the scouring zone, the sensor light intensity is ≥50 lux and the fluctuation coefficient is ≤5%; for the stacking zone, the sensor light intensity is ≤10 lux and the fluctuation coefficient is ≤3%.

2. The offshore wind turbine foundation scour pit morphology monitoring system according to claim 1, characterized in that: The light sensors are spaced 3cm-10cm apart along the axial direction of the pile foundation and 10°-15° apart around the perimeter, with the lens set to a horizontal orientation.

3. The offshore wind turbine foundation scour pit morphology monitoring system according to claim 1, characterized in that: The narrow-spectrum red light sensor is deployed every 15°-20° along the circumference of the pile foundation. The lens axis forms a downward tilt angle of 30°-45° with the normal to the pile foundation surface. The detection range covers the outer wall of the pile foundation to the edge of the accumulation zone with a radius of 1-2 times the pile diameter.

4. The offshore wind turbine foundation scour pit morphology monitoring system according to claim 1, characterized in that: The data processing module includes a slope calculation unit; The slope calculation unit calculates the slope of the scour pit bottom based on the exposure time series data of the light sensor: sensor data from the same circumferential profile are selected and arranged in ascending order of exposure time; the vertical height difference and time difference between adjacent sensors are calculated, and the slope is solved by combining the water erosion advance rate.

5. The offshore wind turbine foundation scour pit morphology monitoring system according to claim 1, characterized in that: The data processing module also includes a stacking thickness calculation unit; The sediment deposition thickness calculation unit calculates the sediment deposition thickness based on the Lambert-Beer law: The narrow-spectrum red light sensor emits a light beam with a wavelength of 630±10nm and receives the light intensity I reflected by accumulated sediment. According to the formula Calculate the thickness d, where The initial reference light intensity is given by k, where k is the local red light absorption coefficient of the sediment. The reflectivity of the mud and sand surface. This refers to the light transmittance of the water body.

6. The offshore wind turbine foundation scour pit morphology monitoring system according to claim 1, characterized in that: The data processing module also includes a fusion unit; The fusion unit unifies the pit bottom slope data, red light reflection intensity data and continuous cross-sectional data into the local coordinate system of the pile foundation through spatiotemporal registration. It uses the iterative nearest point algorithm to register the sonar point cloud and the slope data of the light sensor, and generates the three-dimensional shape of the accumulation body through inverse distance weighted interpolation. It then stitches the data into a full-circumferential asymmetric morphological model that includes the scour pit depth gradient and the accumulation body thickness distribution.

7. A method for monitoring the morphology of scour pits in offshore wind turbine foundations, based on the offshore wind turbine foundation scour pit morphology monitoring system described in any one of claims 1-6, characterized in that, Includes the following steps: S1. An array of optical sensors is arranged along the circumference of the pile foundation, and a sonar scanning module is set on the flow-facing side. The scour zone and the deposition zone are divided by the partition unit. S2. Activate the light sensor of the scour zone to obtain exposure time data, and solve the slope of the scour pit bottom through the slope calculation unit; S3. Activate the narrow-spectrum red light sensor of the sedimentation zone and calculate the thickness of sediment deposition based on the Lambert-Beer law; S4. The sonar scanning module acquires the cross-sectional data of the upstream side, and the fusion unit fuses the three types of data to generate a three-dimensional scour morphology model.

8. The method for monitoring the morphology of scour pits in offshore wind turbine foundations according to claim 7, characterized in that: In step S2, the exposure timing data of the light sensor is recorded by the clock synchronization unit as a time stamp of the sudden increase in light intensity, and associated with preset three-dimensional coordinate parameters to form a scour depth timing signal chain in the exposure order from high to low.

9. A method for monitoring the morphology of scour pits in offshore wind turbine foundations according to claim 7, characterized in that: In step S4, data fusion includes: Sonar point cloud data is converted into three-dimensional rectangular coordinates, and invalid data is removed by wavelet thresholding. The elevation of sonar point clouds is corrected using slope data from light sensors, and the bottom morphology of the uncovered areas is extrapolated. Spatial interpolation of the accumulation thickness data, combined with the accumulation partition boundaries extrapolated by sonar, generates a three-dimensional model of the fan-shaped accumulation body.

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