A method for detecting scour of offshore wind turbine pile foundations based on unmanned boats

Abstract

The present invention belongs to the field of pile foundation detection and discloses a method for detecting scour of offshore wind turbine pile foundations based on an unmanned vessel, comprising: S1, transporting an unmanned submarine carrying a sonar scanning device to a target location; S2, releasing the unmanned submarine onto the sea surface; S3, scanning the wind turbine pile foundation in a circle at a depth of the first scan according to a set scanning distance to obtain a point cloud set of the first scan; S4, the unmanned submarine continuing subsequent scans; S5, the unmanned vessel recovering the unmanned submarine; S6, downloading all point cloud sets from the unmanned submarine; S7, modeling the wind turbine pile foundation based on all point cloud sets to obtain a three-dimensional model of the wind turbine pile foundation; S8, obtaining scour detection data based on the three-dimensional model. The present invention effectively reduces the amount of data and can improve the computational efficiency of subsequent scour detection.

Description

Technical Field

[0001] The present invention relates to the field of pile foundation detection, and in particular to an offshore wind power pile foundation scour detection method based on an unmanned vessel. Background Art

[0002] The continuous erosion of seawater against the foundations of offshore wind farms can destabilize the foundation structure, impacting the safety and operational efficiency of the entire wind farm. Traditionally, detecting erosion in wind turbine pile foundations relies on manual inspections by divers, but this method is costly, inefficient, and carries safety risks.

[0003] With the development of unmanned control technology, the technology of using unmanned ships to conduct scour detection on offshore wind turbine pile foundations has gradually emerged. Usually, the unmanned ship transports an unmanned submarine carrying sonar modeling equipment to the vicinity of the wind turbine pile foundation to be inspected, and then the unmanned submarine carries the sonar modeling equipment to perform underwater modeling of the wind turbine pile foundation. The scour situation is determined by analyzing the obtained model.

[0004] Since the underwater part of the wind turbine pile foundation is generally long, it is usually necessary to scan around the wind turbine pile foundation at different depths, and finally merge the data obtained from scanning at different depths to achieve scanning of the entire wind turbine pile foundation.

[0005] However, the existing technology generally sets the same overlap ratio between the scanning ranges corresponding to two adjacent scanning depths, and does not take into account the different degrees to which different parts of the wind turbine pile foundation are actually affected by scour. This can easily lead to the area of ​​the repeated scan being too large, making the subsequent data fusion time too long, affecting the efficiency of obtaining scour detection results. Summary of the Invention

[0006] The purpose of the present invention is to disclose a method for detecting scour of offshore wind turbine pile foundations based on an unmanned vessel, so as to solve the technical problem of how to determine the overlapping depth between two adjacent scanning depths when scanning the wind turbine pile foundation at different scanning depths, thereby improving the efficiency of obtaining scour detection results.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] The present invention provides an offshore wind power pile foundation scour detection method based on an unmanned vessel, comprising:

[0009] S1, the unmanned ship transports the unmanned submarine carrying the sonar scanning device to the target location;

[0010] S2, the unmanned ship releases the unmanned submarine onto the sea surface;

[0011] S3: The unmanned submarine goes to the preset first scanning depth, and scans the wind turbine pile foundation in a circle at the first scanning depth according to the set scanning distance to obtain a point cloud set of the first scan;

[0012] S4: The unmanned submarine continues the subsequent scan according to the following control method, including:

[0013] S41, initialize the value of k to 1;

[0014] S42, calculate the depth dep of the k+1th scan based on the point cloud set obtained by the kth scan k+1 ;

[0015] S43, determine whether the distance to the seabed is less than the set safety distance, if not, proceed to S44, if so, proceed to S46;

[0016] S44, according to the set scanning distance, at the depth dep of the k+1th scan k+1 Scan around the wind turbine pile foundation to obtain the point cloud set of the k+1th scan;

[0017] S45, add 1 to the value of k and go to S42;

[0018] S46, rise to the sea surface;

[0019] S5, the unmanned ship recovers the unmanned submarine;

[0020] S6, download all point cloud sets from the unmanned submarine;

[0021] S7, modeling the wind turbine pile foundation based on all point cloud sets to obtain a three-dimensional model of the wind turbine pile foundation;

[0022] S8, obtaining scour detection data based on the three-dimensional model.

[0023] Preferably, the target position is a position whose distance from the offshore wind power pile is less than a set distance.

[0024] Preferably, releasing the unmanned submarine onto the sea surface comprises:

[0025] The unmanned ship uses a crane to release the unmanned submarine onto the sea surface.

[0026] Preferably, scanning is performed around the wind power pile foundation, including:

[0027] During the orbit, sound wave pulses are continuously emitted to scan.

[0028] Preferably, the process of determining the preset first scanning depth includes:

[0029] Let d represent the set scanning distance, and depw represent the length of the scanning area in the vertical direction when the object is scanned along the horizontal direction when the distance between the sonar scanning device and the object is d;

[0030] The depth of the first scan is

[0031] Preferably, the depth dep of the k+1th scan is calculated based on the point cloud set obtained by the kth scan. k+1 ,include:

[0032] Establish a three-dimensional coordinate system according to the set rules;

[0033] Sort the points in the point cloud set obtained by the kth scan in descending order of Z-axis coordinates, and put the Z-axis coordinates at the front. The points are stored in the set calu, s is the set value, and nclud represents the total number of points in the point cloud set obtained by the k-th scan;

[0034] Calculate the scan coefficient based on calu;

[0035] Calculate the depth dep of the k+1th scan based on the scan coefficient k+1 .

[0036] Preferably, establishing a three-dimensional coordinate system according to set rules includes:

[0037] A three-dimensional coordinate system is established with the sea level as the plane formed by the X-axis and the Y-axis, and the direction perpendicular to the sea level and pointing to the seabed as the positive direction of the Z-axis.

[0038] Preferably, the scanning coefficient is calculated based on calu, including:

[0039] The scan factor is calculated using the following formula:

[0040]

[0041] depvr k represents the scanning coefficient calculated based on the point cloud set of the k-th scan, clud represents the point cloud set obtained by the k-th scan, wist i represents the distance between point i and the axis of the wind turbine pile foundation, avewist represents the average value of the distance between the points in clud and the axis of the wind turbine pile foundation, wist max Indicates the maximum distance between the point in the clud and the axis of the wind turbine pile foundation, FTU k Indicates the turbidity of seawater at the kth scan, FTU pre represents the preset turbidity, α1 and α2 represent the distance weight and turbidity weight respectively.

[0042] Preferably, the depth dep of the k+1th scan is calculated based on the scan coefficient k+1 ,include:

[0043] Use the following formula to calculate dep k+1 :

[0044]

[0045] dep k It represents the depth of the k-th scan, and depvrc represents the set scan coefficient comparison value.

[0046] Preferably, the unmanned ship recovers the unmanned submarine, comprising:

[0047] The unmanned ship uses a crane to grab the unmanned submarine and recover it.

[0048] Beneficial effects:

[0049] Compared with the prior art, the present invention does not set the same overlap ratio on the scanning ranges of two adjacent scanning depths when performing scour detection on offshore wind turbine pile foundations, but can calculate the scanning depth of the next scan based on the point cloud data obtained in the previous scan, thereby realizing adaptive changes in the scanning depth. When the degree of scouring on the surface of the wind turbine pile foundation at the intersection of the two scanning ranges is more serious, a larger overlap ratio can be used to obtain more point cloud data in the area with severe scouring, thereby providing more effective data for subsequent detection calculations; when the degree of scouring on the surface of the wind turbine pile foundation at the intersection of the two scanning ranges is less serious, a smaller overlap ratio can be used to reduce the amount of point cloud data finally obtained, thereby realizing effective suppression of the data amount and improving the computational efficiency of subsequent scouring detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0051] Figure 1 Schematic diagram of an offshore wind power pile foundation scour detection method based on an unmanned vessel according to the present invention.

[0052] Figure 2 This is a schematic diagram of the process of modeling a wind turbine pile foundation according to the present invention. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0054] The present invention provides an offshore wind power pile foundation scour detection method based on an unmanned vessel, comprising:

[0055] S1, the unmanned ship will transport the unmanned submarine carrying the sonar scanning device to the target location.

[0056] Specifically, the target location is a location near a wind power pile foundation that needs to be inspected.

[0057] Preferably, the target location is a location that is less than a set distance from the offshore wind turbine pile. For example, the set distance is 10 meters. For example, the target location is any point within a circular area with a radius of 10 meters centered on the wind turbine pile foundation.

[0058] S2, the unmanned ship releases the unmanned submarine onto the sea surface.

[0059] Specifically, an area for placing the unmanned submarine is provided at the tail of the unmanned boat. The unmanned boat can be fixed on the unmanned boat by means of a winch or by means of a crane.

[0060] Preferably, releasing the unmanned submarine onto the sea surface comprises:

[0061] The unmanned ship uses a crane to release the unmanned submarine onto the sea surface.

[0062] Specifically, the unmanned ship lifts the unmanned submarine to the sea surface by rotating the crane arm, and then releases the lifting device, and the unmanned submarine falls into the sea surface. The lifting device can be a hook, a clamp, etc.

[0063] In step S3, the unmanned submarine goes to the preset first scanning depth, and scans the wind turbine pile foundation in a circle at the first scanning depth according to the set scanning distance to obtain the point cloud set of the first scan.

[0064] Preferably, the unmanned submarine is provided with an automatic control program, which can control the unmanned submarine to reach the depth of the first scan and scan around the wind power pile foundation.

[0065] After circling once, the unmanned submarine returns to the position where it started scanning at that depth.

[0066] Preferably, scanning is performed around the wind power pile foundation, including:

[0067] During the orbit, sound wave pulses are continuously emitted to scan.

[0068] Preferably, the process of determining the preset first scanning depth includes:

[0069] Let d represent the set scanning distance, and depw represent the length of the scanning area in the vertical direction when the object is scanned along the horizontal direction when the distance between the sonar scanning device and the object is d;

[0070] When scanning the wind turbine pile foundation, the horizontal direction is the direction parallel to the sea level;

[0071] The depth of the first scan is

[0072] Specifically, the sonar scanning device can scan an area at a time. When the sonar scanning device scans toward the wind power pile foundation at a given scanning distance, the scanning area will have a certain width in the vertical direction (ie, the direction perpendicular to the sea level).

[0073] For example, the value of d may be 2 meters.

[0074] Specifically, the process of generating point cloud data is as follows:

[0075] 1. Sonar emits sound waves

[0076] Transmitter: A sonar system's transmitter (often called a sonar array or sonar transmitter) emits one or more sound pulses. These pulses are high-frequency sound waves that can travel great distances through water.

[0077] Pulse Selection: The frequency and duration of the sonar pulses are determined by the sonar system's settings. High-frequency sound waves generally provide better resolution but have a shorter propagation distance, while low-frequency sound waves have a greater propagation distance but lower resolution.

[0078] 2. Sound wave propagation

[0079] Sound wave propagation: Sound waves propagate in water at a certain speed (approximately 1500 m / s, depending on the water temperature, salinity, and pressure). When sound waves encounter objects (such as the seabed or obstacles), they are reflected.

[0080] Propagation path: After the sound wave is emitted from the transmitter, it propagates in a straight line until it encounters the target object (seabed or other object) and is reflected back.

[0081] 3. Sound wave reception

[0082] Receiver: The receiver in a sonar system (usually a sonar array) picks up the sound waves reflected from the target object. The receiver and transmitter can be the same device or separate units.

[0083] Signal processing: Sound waves are attenuated and scattered when they propagate through water. The receiver receives the echo signal and converts it into an electrical signal.

[0084] 4. Signal conversion and processing

[0085] Analog-to-digital conversion: The received analog sound wave signal will be converted into a digital signal through an analog-to-digital converter for further processing and analysis.

[0086] Signal Enhancement: Digital signals are amplified and de-noised to enhance signal quality and clarity. This step improves data resolution and accuracy.

[0087] 5. Data Processing

[0088] Time delay measurement: Sonar systems measure the time difference between the transmission and reception of sound waves. Since the speed of sound waves in water is known, the distance from the target object to the submarine can be calculated from this time delay.

[0089] Distance calculation: Using the propagation speed and time delay of sound waves, the system can calculate the distance the sound waves travel to the target object. This distance is the depth information of the point measured by the sonar.

[0090] 6. Point cloud data generation

[0091] Single-point measurement: A sonar system uses a single acoustic pulse to measure the depth of a single point. Using multiple acoustic beams or pulses, the system can acquire data from multiple points in different directions and locations.

[0092] S4: The unmanned submarine continues the subsequent scan according to the following control method, including:

[0093] S41, initialize the value of k to 1;

[0094] S42, calculate the depth dep of the k+1th scan based on the point cloud set obtained by the kth scan k+1 ;

[0095] S43, determine whether the distance to the seabed is less than the set safety distance, if not, proceed to S44, if so, proceed to S46;

[0096] S44, according to the set scanning distance, at the depth dep of the k+1th scan k+1 Scan around the wind turbine pile foundation to obtain the point cloud set of the k+1th scan;

[0097] S45, add 1 to the value of k and go to S42;

[0098] S46, surfacing to the sea surface. After surfacing, the unmanned ship sends its own location information to the unmanned ship, so that the unmanned ship can go to the area where the unmanned submarine is located based on the location information.

[0099] Specifically, the above control logic is executed by the navigation control device on the unmanned submarine.

[0100] Preferably, the safety distance is set to 0.5 meters.

[0101] Preferably, the depth dep of the k+1th scan is calculated based on the point cloud set obtained by the kth scan. k+1 ,include:

[0102] Establish a three-dimensional coordinate system according to the set rules;

[0103] Sort the points in the point cloud set obtained by the kth scan in descending order of Z-axis coordinates, and put the Z-axis coordinates at the front. The points are stored in the set calu, s is the set value, and nclud represents the total number of points in the point cloud set obtained by the k-th scan;

[0104] Calculate the scan coefficient based on calu;

[0105] Calculate the depth dep of the k+1th scan based on the scan coefficient k+1 .

[0106] Specifically, the set value may be 10.

[0107] Preferably, establishing a three-dimensional coordinate system according to set rules includes:

[0108] A three-dimensional coordinate system is established with the sea level as the plane formed by the X-axis and the Y-axis, and the direction perpendicular to the sea level and pointing to the seabed as the positive direction of the Z-axis.

[0109] Preferably, the scanning coefficient is calculated based on calu, including:

[0110] The scan factor is calculated using the following formula:

[0111]

[0112] depvr k represents the scanning coefficient calculated based on the point cloud set of the k-th scan, clud represents the point cloud set obtained by the k-th scan, wist irepresents the distance between point i and the axis of the wind turbine pile foundation, avewist represents the average value of the distance between the points in clud and the axis of the wind turbine pile foundation, wist max Indicates the maximum distance between the point in the clud and the axis of the wind turbine pile foundation, FTU k Indicates the turbidity of seawater at the kth scan, FTU pre represents the preset turbidity, α1 and α2 represent the distance weight and turbidity weight respectively.

[0113] The scanning coefficient of the present invention is calculated from the distance between the point in the point cloud and the axis, and the turbidity of the seawater during scanning. The greater the fluctuation in the distance between the point in the point cloud and the axis, and the greater the turbidity of the seawater, the larger the scanning coefficient. This reduces the difference between the calculated k+1th and k+1th scanning depths, and increases the area of ​​the repeated scanning when scanning the wind turbine pile foundation at the two scanning depths. This allows more point cloud data to be acquired for areas with large distance variations.

[0114] The smaller the fluctuation in the distance between a point in the point cloud and the axis, and the lower the turbidity of the seawater, the smaller the scanning coefficient. This increases the difference between the calculated k+1th and k+1th scanning depths, and reduces the area of ​​the repeated scans when scanning the wind turbine pile foundation at the two scanning depths. This reduces the number of point clouds.

[0115] Specifically, the axis of a wind turbine pile foundation is a line perpendicular to the sea level where the wind turbine pile foundation is located and passes through the center of the wind turbine pile foundation. Wind turbine pile foundations are generally cylindrical, and the axis of a wind turbine pile foundation is a line passing through the centers of the two end faces of the cylinder formed by the wind turbine pile.

[0116] Preferably, the preset turbidity is 30.

[0117] Preferably, the distance weight and turbidity weight are 0.7 and 0.3, respectively.

[0118] Preferably, the depth dep of the k+1th scan is calculated based on the scan coefficient k+1 ,include:

[0119] Use the following formula to calculate dep k+1 :

[0120]

[0121] dep k It represents the depth of the k-th scan, and depvrc represents the set scan coefficient comparison value.

[0122] Specifically, the difference between the depth of the k+1th scan and the depth of the kth scan can vary with the scan coefficient. The larger the scan coefficient, the smaller the difference, while the smaller the scan coefficient, the larger the difference. In this way, the difference between two adjacent scan depths can be adaptively varied with the scan coefficient, allowing more point cloud data to be obtained for severely eroded areas while reducing the overall amount of point cloud data obtained.

[0123] If the existing technology is used, the value between two adjacent scanning depths will be a fixed value, which may easily lead to the situation where too many point clouds are repeatedly acquired in areas that are less affected by scour.

[0124] Specifically, the set scanning coefficient contrast value may be 1.01.

[0125] If the existing fixed distance method is used, the bracketed part of the above formula is generally a small value, such as 0.6, which will cause the repeated area to be too large.

[0126] S5, unmanned ship recovers unmanned submarine.

[0127] Specifically, the unmanned ship can recover the unmanned submarine through robotic arms, fishing nets, etc.

[0128] Preferably, the unmanned ship recovers the unmanned submarine, comprising:

[0129] The unmanned ship uses a crane to grab the unmanned submarine and recover it.

[0130] A grabbing device is installed on the boom, and the grabbing device grabs a device set on the top of the unmanned submarine and used to cooperate with the grabbing device, thereby connecting the unmanned submarine to the boom.

[0131] S6, download all point cloud collections from the unmanned submarine.

[0132] Specifically, the host computer can communicate with the unmanned submarine through a wireless connection or a wired connection, thereby downloading the point cloud collection obtained at all scanning depths from the unmanned submarine.

[0133] S7, modeling the wind turbine pile foundation based on all point cloud sets to obtain a three-dimensional model of the wind turbine pile foundation.

[0134] Specifically, before modeling, all point cloud data are unified in coordinates.

[0135] Preferably, if Figure 2 As shown, the wind turbine pile foundation is modeled based on all point cloud sets to obtain a three-dimensional model of the wind turbine pile foundation, including:

[0136] Denoise the points in each point cloud set respectively to obtain a denoised point cloud set;

[0137] Fuse all denoised point cloud sets to obtain a fused point cloud;

[0138] The wind turbine pile foundation is modeled based on the fused point cloud to obtain a three-dimensional model of the wind turbine pile foundation.

[0139] Preferably, denoising is performed on each point in each point cloud set, including:

[0140] Denoise each point in the point cloud set from the X-axis direction, Y-axis direction, and Z-axis direction respectively to obtain the X-axis coordinate, Y-axis coordinate, and Z-axis coordinate of each point in the point cloud set after denoising.

[0141] Preferably, performing noise reduction on each point in the point cloud set from the X-axis direction to obtain the X-axis coordinate of each point in the point cloud set after noise reduction includes:

[0142] On the plane formed by the Y axis and the Z axis, the X-axis coordinate of the point in the point cloud is used as the pixel value to generate the image PX;

[0143] Use the following method to denoise each pixel in PX and obtain the X-axis coordinate of each pixel after denoising:

[0144] Calculate the coefficient of variation of the pixel value of the pixel point in PX;

[0145] If the coefficient of variation is greater than the set coefficient of variation threshold, the first noise reduction algorithm is used to perform noise reduction on each pixel point in PX respectively, and the pixel value after noise reduction of each pixel point is obtained, and the pixel value after noise reduction is used as the X-axis coordinate after noise reduction; otherwise, the second noise reduction algorithm is used to perform noise reduction on each pixel point in PX respectively, and the pixel value after noise reduction of each pixel point is obtained, and the pixel value after noise reduction is used as the X-axis coordinate after noise reduction.

[0146] Preferably, performing noise reduction on each point in the point cloud set from the Y-axis direction to obtain the Y-axis coordinate of each point in the point cloud set after noise reduction includes:

[0147] On the plane formed by the X-axis and the Z-axis, the Y-axis coordinates of the points in the point cloud are used as pixel values ​​to generate an image PY;

[0148] Use the following method to denoise each pixel in PY and obtain the Y-axis coordinate of each pixel after denoising:

[0149] Calculate the coefficient of variation of the pixel value of the pixel point in PY;

[0150] If the variation coefficient is greater than the set variation coefficient threshold, the first noise reduction algorithm is used to reduce the noise of each pixel in PY respectively, and the pixel value after noise reduction is obtained for each pixel, and the pixel value after noise reduction is used as the Y-axis coordinate after noise reduction; otherwise, the second noise reduction algorithm is used to reduce the noise of each pixel in PY respectively, and the pixel value after noise reduction is obtained for each pixel, and the pixel value after noise reduction is used as the Y-axis coordinate after noise reduction.

[0151] Preferably, performing noise reduction on each point in the point cloud set from the Z-axis direction to obtain the Z-axis coordinate of each point in the point cloud set after noise reduction includes:

[0152] On the plane formed by the X-axis and the Y-axis, the Z-axis coordinates of the points in the point cloud are used as pixel values ​​to generate an image PZ;

[0153] Use the following method to denoise each pixel in PZ and obtain the Z-axis coordinate of each pixel after denoising:

[0154] Calculate the coefficient of variation of the pixel values ​​of the pixels in PZ;

[0155] If the variation coefficient is greater than the set variation coefficient threshold, the first noise reduction algorithm is used to reduce the noise of each pixel in PZ respectively, and the pixel value after noise reduction of each pixel is obtained, and the pixel value after noise reduction is used as the Z-axis coordinate after noise reduction; otherwise, the second noise reduction algorithm is used to reduce the noise of each pixel in PZ respectively, and the pixel value after noise reduction of each pixel is obtained, and the pixel value after noise reduction is used as the Z-axis coordinate after noise reduction.

[0156] Preferably, the calculation formula of the coefficient of variation is:

[0157]

[0158] vrch represents the coefficient of change of Pa, PXU represents the set of pixels in Pa, NPXU represents the total number of pixels in PXU, pixelv j Indicates the pixel value of pixel j, pixelv max represents the maximum value of the pixel value in PXU, Nbi represents the total number of pixels in PXU whose pixel value is greater than all pixels in the 8-neighborhood, β1 is the pixel value distribution weight, β2 is the pixel value difference weight, Pa∈{PX,PY,PZ}.

[0159] Specifically, the coefficient of variation of the present invention can effectively represent the magnitude of the variation in pixel values ​​in Pa from two different perspectives. The coefficient of variation increases when the standard deviation of the pixel values ​​in Pa is greater and the number of pixels with values ​​greater than all pixels in the 8-neighborhood increases. Conversely, the coefficient of variation decreases. This allows the selection of an appropriate noise reduction algorithm for PX based on the coefficient of variation, thereby avoiding the need to use the same algorithm for noise reduction in each point in the point cloud set in the X, Y, and Z directions. One of these three directions contains the most information, while the differences in coordinate values ​​in the other directions are smaller. Therefore, the present invention can use an algorithm with greater noise reduction effectiveness, but longer denoising time, when the coefficient of variation is greater (i.e., when the probability that Pa belongs to the direction containing the most information is greater). For the other directions, more efficient algorithms are used, thereby ensuring the effectiveness of noise reduction while improving overall noise reduction efficiency.

[0160] Preferably, the pixel value distribution weight is 0.6, and the pixel value difference weight is 0.4.

[0161] Preferably, the set variation coefficient threshold is 0.7.

[0162] Preferably, the first noise reduction algorithm is a bilateral filtering algorithm, and the second noise reduction algorithm is a Gaussian filtering algorithm.

[0163] Specifically, the first noise reduction algorithm may also be a guided filtering algorithm, an anisotropic diffusion filtering algorithm, or the like.

[0164] The second noise reduction algorithm may also be a mean filter algorithm or the like.

[0165] The first denoising algorithm is a class of algorithms that can reduce image noise while preserving image edge details. Traditional denoising algorithms such as mean filtering and Gaussian filtering tend to blur edges, while the first denoising algorithm can identify and preserve important structure and edge information in the image.

[0166] The process of fusing a collection of point clouds includes:

[0167] 1. Coordinate system conversion and alignment:

[0168] Different scanning distances: Scanning at different distances will result in different position and density of point cloud data. Therefore, the point cloud data must first be converted to a common coordinate system. Typically, the scanning device provides its own location information or uses an external positioning system (such as GPS or IMU) to record the device's position and orientation during each scan.

[0169] If there is no direct spatial reference between devices, algorithms such as ICP (Iterative Closest Point) are needed to align point cloud data collected from different perspectives or distances.

[0170] 2. Point Cloud Registration:

[0171] Accurate registration is the core of point cloud fusion. The goal of registration is to perfectly align data from different scanning positions. There are two common registration methods:

[0172] Coarse registration: Perform preliminary point cloud alignment using known landmarks, sensor positions, or manually selected reference points.

[0173] Fine registration: Based on coarse registration, algorithms such as ICP are used to further optimize the point cloud data to align them more precisely. ICP iteratively calculates the distance and error between point clouds, gradually adjusting the position, rotation, and scale of the point clouds until the error is minimized.

[0174] 3. Overlapping area optimization

[0175] Different scanning distances may overlap in some areas. The following methods can be used to deal with these overlapping areas:

[0176] Method: The points in the overlapping area can be merged based on a simple averaging strategy, that is, for each group of similar points in the overlapping area, their average position is taken as the new point.

[0177] S8, obtaining scour detection data based on the three-dimensional model.

[0178] Specifically, the newly obtained three-dimensional model A is compared with the three-dimensional model B generated during the last scour detection, and the regions in the three-dimensional model A that are different from B are obtained. The volumes of the different regions are obtained respectively, thereby obtaining scour detection data.

[0179] When performing scour detection on offshore wind turbine pile foundations, the same overlap ratio is not set on the scanning ranges of two adjacent scanning depths. Instead, the scanning depth of the next scan can be calculated based on the point cloud data obtained in the previous scan, thereby realizing adaptive changes in the scanning depth. When the degree of scouring on the surface of the wind turbine pile foundation at the intersection of the two scanning ranges is more serious, a larger overlap ratio is used to obtain more point cloud data in the area with severe scouring, thereby providing more effective data for subsequent detection calculations; when the degree of scouring on the surface of the wind turbine pile foundation at the intersection of the two scanning ranges is less serious, a smaller overlap ratio is used to reduce the amount of point cloud data finally obtained, thereby realizing effective suppression of the data amount and improving the calculation efficiency of subsequent scour detection.

[0180] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to the specific embodiments described. Obviously, many modifications and variations are possible based on the content of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for detecting scour of offshore wind power pile foundation based on an unmanned vessel, characterized in that: include: S1, the unmanned ship transports the unmanned submarine carrying the sonar scanning device to the target location; S2, the unmanned ship releases the unmanned submarine onto the sea surface; S3: The unmanned submarine goes to the preset first scanning depth, and scans the wind turbine pile foundation in a circle at the first scanning depth according to the set scanning distance to obtain a point cloud set of the first scan; S4: The unmanned submarine continues the subsequent scan according to the following control method, including: S41, initialize the value of k to 1; S42, calculate the depth dep of the k+1th scan based on the point cloud set obtained by the kth scan k+1 ,include: Establish a three-dimensional coordinate system according to the set rules; Sort the points in the point cloud set obtained by the kth scan in descending order of Z-axis coordinates, and put the Z-axis coordinates at the front. The points are stored in the set calu, s is the set value, and nclud represents the total number of points in the point cloud set obtained by the k-th scan; Calculate the scan coefficients based on calu, including: The scan factor is calculated using the following formula: depvr k represents the scanning coefficient calculated based on the point cloud set of the k-th scan, clud represents the point cloud set obtained by the k-th scan, wist i represents the distance between point i and the axis of the wind turbine pile foundation, avewist represents the average value of the distance between the points in clud and the axis of the wind turbine pile foundation, wist max Indicates the maximum distance between the point in the clud and the axis of the wind turbine pile foundation, FTU k Indicates the turbidity of seawater at the kth scan, FTU pre represents the preset turbidity, α1 and α2 represent the distance weight and turbidity weight respectively; Calculate the depth dep of the k+1th scan based on the scan coefficient k+1 ,include: Use the following formula to calculate dep k+1 : dep k Indicates the depth of the k-th scan, depvrc indicates the set scan coefficient comparison value; S43, determine whether the distance to the seabed is less than the set safety distance, if not, proceed to S44, if so, proceed to S46; S44, according to the set scanning distance, at the depth dep of the k+1th scan k+1 Scan around the wind turbine pile foundation to obtain the point cloud set of the k+1th scan; S45, add 1 to the value of k and go to S42; S46, rise to the sea surface; S5, the unmanned ship recovers the unmanned submarine; S6, download all point cloud sets from the unmanned submarine; S7, modeling the wind turbine pile foundation based on all point cloud sets to obtain a three-dimensional model of the wind turbine pile foundation; S8, obtaining scour detection data based on the three-dimensional model.

2. The offshore wind power pile foundation scour detection method based on an unmanned vessel according to claim 1 is characterized in that: The target position is a position where the distance to the offshore wind power pile is less than a set distance.

3. The offshore wind power pile foundation scour detection method based on an unmanned vessel according to claim 1 is characterized in that: Release the unmanned submarine onto the sea surface, including: The unmanned ship uses a crane to release the unmanned submarine onto the sea surface.

4. The offshore wind power pile foundation scour detection method based on an unmanned vessel according to claim 1, characterized in that: Scan around the wind turbine pile foundation, including: During the orbit, sound wave pulses are continuously emitted to scan.

5. The offshore wind power pile foundation scour detection method based on an unmanned vessel according to claim 1, characterized in that: The process of determining the preset first scanning depth includes: Let d represent the set scanning distance, and depw represent the length of the scanning area in the vertical direction when the object is scanned along the horizontal direction when the distance between the sonar scanning device and the object is d; The depth of the first scan is 6. The offshore wind power pile foundation scour detection method based on an unmanned vessel according to claim 1, characterized in that: Establish a three-dimensional coordinate system according to the set rules, including: A three-dimensional coordinate system is established with the sea level as the plane formed by the X-axis and the Y-axis, and the direction perpendicular to the sea level and pointing to the seabed as the positive direction of the Z-axis.

7. The offshore wind power pile foundation scour detection method based on an unmanned vessel according to claim 1, characterized in that: Unmanned boats recover unmanned submarines, including: The unmanned ship uses a crane to grab the unmanned submarine and recover it.

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