Multi-beam sounding yawing deviation detection and correction method

Abstract

The invention relates to a multi-beam sounding yawing deviation detection and correction method. The method comprises the following steps: acquiring a normal vector of a wind power pile; performing point cloud segmentation on the point cloud data of the wind power pile body according to the normal vector of the wind power pile to obtain a point cloud segmentation area of the wind power pile; obtaining a final model of the wind power pile based on the shape of the cylinder of the wind power pile and the point cloud segmentation area of the wind power pile; and calculating the yawing deviation according to the final model and the transducer data. The invention relates to a method for detecting and correcting yawing deviation in multi-beam sounding. The problems that in the prior art, yawing deviation calibration work of multi-beam sonar data mainly depends on professional software for processing by professionals or strip central beam point coordinates serve as a rotation center in a yawing deviation correction model, so that the precision of a measurement result is low, and accurate positioning of a wind power pile is affected can be solved. The problems that continuity and integrity of topographic surveying and mapping are lacked, and follow-up construction design, monitoring evaluation and maintenance work are difficult to carry out accurately are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of ocean surveying and mapping, and in particular to a method for detecting and correcting a multi-beam bathymetric bow roll deviation. Background Art

[0002] Due to its high efficiency and high precision, the multi-beam bathymetry system has become the main technical means in seabed topography mapping and marine engineering. Especially in the construction of offshore wind farms, this technology is widely used to monitor the changes in the terrain around the wind turbine pile foundation. However, in practical applications, the installation deviation of the multi-beam bathymetry system, especially the bow roll deviation, will have a significant impact on the accuracy of the measurement data. Bow roll deviation refers to the angular error between the multi-beam transducer and the actual heading of the ship. This deviation will cause a systematic rotational misalignment of the point cloud data.

[0003] In the existing technology, the calibration of the heading deviation of multi-beam sonar data mainly relies on professionals using professional software for processing. This process has high requirements on the experience and professional quality of the operators. In the heading deviation correction model, the coordinates of the central beam point of the strip are used as the rotation center, resulting in low accuracy of the measurement results, affecting the precise positioning of the wind turbine piles, resulting in the lack of continuity and integrity of terrain mapping, and subsequent construction design, monitoring and evaluation, and maintenance work are difficult to carry out accurately.

[0004] Therefore, the prior art has defects and needs to be improved and developed. Summary of the invention

[0005] An embodiment of the invention provides a method for detecting and correcting the bow roll deviation of a multi-beam sounding, which is used to solve the problem that the bow roll deviation calibration work of multi-beam sonar data in the prior art mainly relies on professionals using professional software for processing. This process has high requirements on the experience and professional quality of the operators. In the bow roll deviation correction model, the coordinates of the central beam point of the strip are used as the rotation center, resulting in low accuracy of the measurement result, affecting the precise positioning of the wind turbine piles, resulting in the lack of continuity and integrity in terrain surveying and mapping, and subsequent construction design, monitoring and evaluation, and maintenance work are difficult to carry out accurately.

[0006] The embodiment of the present invention provides a method for detecting and correcting a multi-beam bathymetric bow deviation, comprising:

[0007] S1. Obtain the normal vector of the wind power pile;

[0008] S2. According to the normal vector of the wind turbine pile, the point cloud data of the wind turbine pile body is segmented to obtain the point cloud segmentation area of ​​the wind turbine pile;

[0009] S3, obtaining the final model of the wind power pile based on the shape of the wind power pile cylinder and the wind power pile point cloud segmentation area;

[0010] S4. Calculating the yaw deviation according to the final model and the transducer data.

[0011] Furthermore, the step of performing point cloud segmentation on the wind power pile body point cloud data according to the wind power pile normal vector to obtain the wind power pile point cloud segmentation area includes:

[0012] Select the seed point in the wind power pile point cloud data as the starting point;

[0013] According to the normal vector of the wind turbine pile, the normal direction and curvature of the seed point and adjacent points are obtained;

[0014] Compare the seed point and the adjacent points, and add the adjacent points with similar normal directions and curvatures to the wind power pile point cloud segmentation area 2

[0015] The point cloud data of the wind turbine pile body is processed iteratively until there are no points that meet the requirements of similar normal directions of the seed point and adjacent points and similar curvatures of the seed point and adjacent points, thus completing the point cloud segmentation.

[0016] Furthermore, the condition for the normal directions of the seed point and the adjacent points to be similar is that the angle between the normal vector of the seed point and the normal vector of the adjacent point is between [5°, 15°].

[0017] Furthermore, the condition for the curvature of the seed point and the adjacent points to be similar is that the curvature difference between the seed point and the adjacent points does not exceed 0.01.

[0018] Furthermore, the final model of the wind power pile is obtained based on the shape of the wind power pile cylinder and the wind power pile point cloud segmentation area, including:

[0019] Performing coordinate transformation on the point cloud in the wind power pile point cloud segmentation area to obtain the wind power pile in a two-dimensional coordinate system, so that the axis of the wind power pile cylinder is parallel to the vertical direction in the coordinate system after the coordinate transformation, and the wind power pile cylinder is circular in the two-dimensional coordinate system;

[0020] Establish an objective function based on the sum of squares of the distances from the point cloud points to the outer contour of the wind pile cylinder. Use the gradient descent algorithm to iteratively adjust the parameters of the wind pile cylinder model until the residual function used to quantify the total deviation between the point cloud points and the wind pile cylinder model converges.

[0021] The model with the smallest error in the fitted wind turbine pile cylindrical model is taken as the final model, wherein the error refers to the distance from the point cloud point in the fitted wind turbine pile cylindrical model to the outer contour of the wind turbine pile cylinder.

[0022] Further, the calculating the yaw deviation according to the final model and the transducer data includes:

[0023] Randomly select the final models of two wind farm piles, and use the centers of the final models of the two wind farm piles as point A and point B respectively.

[0024] According to the final models of the two wind farms, the distance from each point on the final model to the corresponding transducer position at the launch time is calculated, and the transducer position with the smallest distance is taken as the rotation center, that is, O 1 Dot and O 2 point;

[0025] Calculate O separately 1 A and O 2 The length of B;

[0026] Assuming that point S is the actual position of the geometric center of the wind turbine pile without the influence of the pitch deviation, according to point A, point B, point O 1 Dot, O 2 Dot, O 1 A and O 2 B. Calculate the coordinates of point S. The coordinate formula of point S is as follows:

[0027]

[0028] Among them, x A ,y A are the horizontal and vertical coordinates of point A;

[0029] x B ,y B are the horizontal and vertical coordinates of point B;

[0030] x S ,y S is the horizontal and vertical coordinates of point S;

[0031] According to O 1 The coordinates of point A and point S are calculated from O 1 The three sides of the triangle formed by point A, point S, that is, O 1 A.O 1 S, the length of SA;

[0032] According to O 1 A.O 1 S, SA length, calculate the cosine value of the heading deviation cosheading, the calculation formula is as follows:

[0033]

[0034] According to the calculated cosine value of the heading deviation, the heading deviation is obtained through the inverse trigonometric function and the non-negativity of the heading deviation.

[0035] Further, the cosine value of the yaw deviation obtained by calculation is used to obtain the yaw deviation through an inverse trigonometric function and the non-negativity of the yaw deviation, including:

[0036] Taking the yaw deviation as a correction item;

[0037] adjusting the position of the transducer according to the correction item;

[0038] Update the final model based on the adjusted transducer position:

[0039] The yaw deviation is iteratively processed until two accurate models are obtained, wherein the accurate models are the most recently updated models of the final model, and the two accurate models correspond one-to-one to the two final models.

[0040] Further, adjusting the position of the transducer according to the correction item includes:

[0041] Define the correction term as Δθ2

[0042] Correct O according to the correction item 1 Dot and O 2 The coordinates of the transducer corresponding to the point O′ are obtained 1 Point and O′ 2

[0043] Point, the correction formula is as follows:

[0044]

[0045] Among them, O 1x , O 1y O 1 The horizontal and vertical coordinates of the point;

[0046] O 2x , O 2y O 2 The horizontal and vertical coordinates of the point;

[0047] O′ 1x , O′ 1y O′ 1 The horizontal and vertical coordinates of the point;

[0048] O′ 2x , O′ 2y O′ 1 The horizontal and vertical coordinates of the point;

[0049] According to the corrected coordinates of the transducer, the transducer position is adjusted.

[0050] Further, the iterative processing of the yaw deviation until two accurate models are obtained, the accurate models being the most recently updated models of the final model, and the two accurate models corresponding to the two final models one by one, comprises:

[0051] Define the water depth as H, the center of the precise model as A 1 The distance between point A and the final model is D 1 , the center of the precise model B 1 The distance between point D and point B of the final model is D 2 , the termination condition of the iterative process is: D 1 <H×0.5% and D 2 <H×0.5%.

[0052] Beneficial effects:

[0053] It can be seen from the above technical solutions that the present invention provides a method for detecting and correcting the bow roll deviation in multi-beam bathymetry, 1. Realizing automated deviation detection: extracting target features and detecting bow roll deviation through point cloud segmentation and cylinder fitting. 2. Improving measurement accuracy: iteratively optimizing the cylindrical model and processing the bow roll deviation twice to reduce the deviation error. 3. Simplifying the calculation process: simplifying the complex three-dimensional fitting problem into a two-dimensional linear fitting through coordinate transformation to reduce the calculation complexity. 4. Enhancing applicability: It is suitable for offshore wind power piles and other complex marine engineering scenarios, and can provide stable high-precision measurements in dynamic environments.

[0054] It should be appreciated that all combinations of the foregoing concepts, as well as additional concepts described in greater detail below, may be considered to be part of the inventive subject matter of the present disclosure, provided such concepts are not mutually inconsistent.

[0055] The foregoing and other aspects, embodiments and features of the present invention can be more fully understood from the following description in conjunction with the accompanying drawings. Other additional aspects of the present invention, such as the features and / or beneficial effects of the exemplary embodiments, will be apparent from the following description or learned from the practice of the specific embodiments according to the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings are not drawn to scale according to actual reference objects. In the accompanying drawings, each identical or nearly identical component shown in various figures may be represented by the same reference numeral. For the sake of clarity, not every component is labeled in each figure. Now, embodiments of various aspects of the present invention will be described by way of example and with reference to the accompanying drawings, in which:

[0057] Figure 1 The present invention is a flowchart of a method for detecting and correcting a multi-beam bathymetric bow roll deviation in an embodiment of the present application.

[0058] Figure 2 This is a demonstration diagram of calculating the heading deviation of a multi-beam bathymetric heading deviation detection and correction method in an embodiment of the present application.

[0059] Figure 3 This is a simulation experiment data diagram of calculating the heading deviation of a multi-beam bathymetric heading deviation detection and correction method in an embodiment of the present application.

[0060] Figure 4 This is a simulation experiment data correction diagram of a multi-beam bathymetric bow roll deviation detection and correction method in an embodiment of the present application.

[0061] Figure 5 This is a graph of measured data of a method for detecting and correcting a multi-beam sounding bow roll deviation in an embodiment of the present application.

[0062] Figure 6 This is a correction diagram of actual experimental data of a method for detecting and correcting a multi-beam bathymetric bow roll deviation in an embodiment of the present application. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Unless otherwise defined, the technical terms or scientific terms used herein should be the common meaning understood by people with general skills in the field to which the present invention belongs.

[0064] The words "first", "second" and similar words used in the patent application specification and claims of the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, unless the context clearly indicates otherwise, the singular forms of "a", "an" or "the" and other similar words do not indicate a quantitative limitation, but indicate the existence of at least one. Words such as "include" or "comprise" mean that the elements or objects appearing before "include" or "comprise" cover the features, wholes, steps, operations, elements and / or components listed after "include" or "comprise", and do not exclude the existence or addition of one or more other features, wholes, steps, operations, elements, components and / or their collections. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0065] In the prior art, the calibration of the heading deviation of multi-beam sonar data mainly relies on professionals using professional software for processing. This process has high requirements on the experience and professional quality of the operators. In the heading deviation correction model, the coordinates of the central beam point of the strip are used as the rotation center, resulting in low accuracy of the measurement results, affecting the precise positioning of the wind turbine piles, resulting in the lack of continuity and integrity of terrain mapping, and making it difficult to accurately carry out subsequent construction design, monitoring and evaluation, and maintenance work.

[0066] In view of this, an embodiment of the present invention provides a method for detecting and correcting a multi-beam sounding bow roll deviation, referring to Figure 1 ,include:

[0067] S1. Obtain the normal vector of the wind power pile;

[0068] S2. According to the normal vector of the wind turbine pile, the point cloud data of the wind turbine pile body is segmented to obtain the point cloud segmentation area of ​​the wind turbine pile;

[0069] S3, obtaining the final model of the wind power pile based on the shape of the wind power pile cylinder and the wind power pile point cloud segmentation area;

[0070] S4. Calculate the heading deviation based on the final model and transducer data.

[0071] The embodiment of the present invention is based on multi-beam bathymetry technology. By acquiring the normal vector of the wind turbine pile and segmenting the point cloud data, the target point cloud area of ​​the wind turbine pile is extracted, and the final model is fitted in combination with the geometric characteristics of the cylinder. The bow roll deviation is calculated based on the geometric relationship between the final model and the transducer data. By segmenting the point cloud data of the wind turbine pile and fitting the final model of the wind turbine pile, the target features can be efficiently extracted and the bow roll deviation can be accurately calculated, providing a basis for subsequent corrections, simplifying the data processing process, and improving the deviation detection accuracy.

[0072] In some embodiments, the point cloud data of the wind power pile body is segmented according to the normal vector of the wind power pile to obtain the point cloud segmentation area of ​​the wind power pile, including:

[0073] Select the seed point in the wind power pile point cloud data as the starting point;

[0074] According to the normal vector of the wind turbine pile, the normal direction and curvature of the seed point and adjacent points are obtained;

[0075] Compare the seed points and the adjacent points, and add the adjacent points with similar normal directions and curvatures to the wind pile point cloud segmentation area; the selection of adjacent points can be based on the distance criterion, selecting the points with a Euclidean distance from the seed point less than the set threshold, or based on the topological relationship, in the connection structure of the point cloud, such as the octree, KD tree, etc., the points directly connected to the seed point are regarded as adjacent points. The wind pile point cloud segmentation area refers to the area composed of the seed points and adjacent points that simultaneously meet the similar normal directions of the seed points and adjacent points and the similar curvatures of the seed points and adjacent points. The normal directions of the seed points and adjacent points can be calculated by calculating the angle between the normal vector of the seed point and the normal vector of the adjacent point. When the angle is between [5°, 15°], the normal directions of the seed points and adjacent points are considered to be similar. The curvature similarity of the seed points and adjacent points can be calculated by calculating the curvature difference between the adjacent points and the seed points. When the curvature difference does not exceed 0.01, the curvature of the seed points and adjacent points is considered to be similar.

[0076] Iteratively process the point cloud data of the wind turbine pile until there are no points that meet the similar normal direction of the seed point and the adjacent points and the similar curvature of the seed point and the adjacent points, and then complete the point cloud segmentation. Effectively segment the multi-beam bathymetric point cloud of the offshore wind turbine pile from the point cloud data.

[0077] By using the normal vector of the wind turbine pile and combining the normal direction and curvature similarity between the seed point and the adjacent points, the point cloud segmentation area is gradually expanded. Adjacent points are selected by distance criteria and topological relationships, and whether to add them to the segmentation area is determined according to the threshold conditions. The target area in the wind turbine pile point cloud data is effectively extracted, noise points and redundant points are excluded, and the accuracy and efficiency of point cloud segmentation are improved. The segmentation method based on the normal vector and curvature characteristics is combined with the regional growing algorithm to achieve efficient point cloud segmentation.

[0078] In some embodiments, the condition for the normal directions of the seed point and the adjacent points to be similar is that the angle between the normal vector of the seed point and the normal vector of the adjacent point is between [5°, 15°].

[0079] In some embodiments, the condition that the curvatures of the seed point and the adjacent points are similar is that the curvature difference between the seed point and the adjacent points does not exceed 0.01.

[0080] In some embodiments, based on the shape of the wind power pile cylinder and the wind power pile point cloud segmentation area, a final model of the wind power pile is obtained, including:

[0081] The point cloud in the wind turbine pile point cloud segmentation area is transformed to obtain the wind turbine pile in the two-dimensional coordinate system, so that the axis of the wind turbine pile cylinder is parallel to the vertical direction in the coordinate system after the coordinate transformation, and the wind turbine pile cylinder is circular in the two-dimensional coordinate system; when the selected seed point is N, where N is a natural number greater than 1, N wind turbine pile point cloud segmentation areas will be obtained, and at this time, each wind turbine pile point cloud segmentation area needs to be transformed. The axis of the wind turbine pile cylinder is parallel to the vertical direction in the coordinate system after the coordinate transformation, thereby simplifying the three-dimensional nonlinear fitting problem to a two-dimensional linear fitting problem.

[0082] Establish an objective function based on the sum of squares of the distances from the point cloud points to the outer contour of the wind pile cylinder. Use the gradient descent algorithm to iteratively adjust the parameters of the wind pile cylinder model until the residual function used to quantify the total deviation between the point cloud points and the wind pile cylinder model converges.

[0083] The model with the smallest error in the fitted wind turbine pile cylindrical model is taken as the final model, where the error refers to the distance from the point cloud point in the fitted wind turbine pile cylindrical model to the outer contour of the wind turbine pile cylinder. Since the wind turbine pile point cloud segmentation area is segmented from the wind turbine pile body point cloud data, the more seed points are selected, the more wind turbine pile point cloud segmentation areas are obtained, and the more wind turbine pile target point clouds are extracted, thereby reducing the computational complexity, improving the efficiency and accuracy of point cloud analysis, and providing a standardized coordinate basis for subsequent steps.

[0084] The axis of the cylinder is aligned with the vertical direction through coordinate transformation to simplify the fitting problem. The cylinder model parameters are adjusted iteratively, and the final fitting model is determined based on the convergence of the residual function. The three-dimensional nonlinear fitting problem is simplified to a two-dimensional linear fitting, which improves the computational efficiency and ensures the accuracy of the fitting model. By combining coordinate transformation with the gradient descent algorithm, efficient point cloud cylinder model fitting is achieved to ensure the minimum model error.

[0085] In some embodiments, the yaw deviation is calculated based on the final model and the transducer data, referring to Figure 2 , which includes:

[0086] Randomly select the final models of two wind turbine piles, and use the centers of the final models of the two wind turbine piles as point A and point B respectively;

[0087] According to the final models of the two wind farms, the distance from each point on the final model to the corresponding transducer position at the launch time is calculated, and the transducer position with the smallest distance is taken as the rotation center, that is, O 1 Dot and O 2 point;

[0088] Calculate O separately 1 A and O 2The length of B;

[0089] Assuming that point S is the actual position of the geometric center of the wind turbine pile without the influence of the pitch deviation, according to point A, point B, point O 1 Dot, O 2 Dot, O 1 A and O 2 B. Calculate the coordinates of point S. The coordinate formula of point S is as follows:

[0090]

[0091] Among them, x A ,y A are the horizontal and vertical coordinates of point A;

[0092] x B ,y B are the horizontal and vertical coordinates of point B;

[0093] x S ,y S is the horizontal and vertical coordinates of point S;

[0094] According to O 1 The coordinates of point A and point S are calculated from O 1 The three sides of the triangle formed by point A, point S, that is, O 1 A.O 1 S, the length of SA;

[0095] According to O 1 A.O 1 S, SA length, calculate the cosine value of the heading deviation cosheading, the calculation formula is as follows:

[0096]

[0097] According to the calculated cosine value of the heading deviation, the heading deviation is obtained through the inverse trigonometric function and the non-negativity of the heading deviation.

[0098] The centers of two cylindrical models are selected as reference points in the two measurement strips, and the geometric relationship is calculated in combination with the transducer position to deduce the true position of the wind pile. The yaw deviation is calculated by the geometric formula. The true geometric position and yaw deviation of the wind pile are accurately deduced by using the model relationship in the two measurement strips, providing a basis for deviation correction. An algorithm for deriving yaw deviation based on the geometric relationship of multiple measurement strips is proposed, which improves the accuracy of deviation calculation.

[0099] In some embodiments, according to the calculated cosine value of the yaw deviation, the yaw deviation is obtained by using an inverse trigonometric function and the non-negativity of the yaw deviation, including:

[0100] Take the heading deviation as the correction item;

[0101] Adjust the position of the transducer according to the correction item;

[0102] updating the final model according to the adjusted transducer position;

[0103] Iterate the yaw deviation until two accurate models are obtained. The accurate model is the last updated model of the final model. The two accurate models correspond to the two final models one by one. The one-to-one correspondence between the two accurate models and the two final models means that the final model with the center of the circle at point A is updated to the model with the center of the circle at point A. 1 The final model of the circle with the center at point B is updated to the circle with the center at point B. 1 The exact model of the point.

[0104] The obtained bow deviation is an approximate value of the bow deviation obtained in the case of rough detection. Therefore, the bow deviation is used as a correction term to adjust the position of the transducer and update the model, and iterative processing is performed until an accurate model corresponding to the final model is obtained, thereby achieving precise detection of the bow deviation. By dynamically correcting the transducer position and updating the model, the bow deviation value is gradually optimized to ensure the accuracy of the correction result. An iterative optimization method based on the deviation correction term is proposed to improve the accuracy of the deviation correction and the consistency of the model.

[0105] In some embodiments, adjusting the position of the transducer according to the correction term includes:

[0106] Define the correction term as Δθ;

[0107] Corrected according to the correction item O 1 Dot and O 2 The coordinates of the transducer corresponding to the point O′ are obtained 1 Point and O′ 2 Point, the correction formula is as follows:

[0108]

[0109] Among them, O 1x , O 1y O 1 The horizontal and vertical coordinates of the point;

[0110] O 2x , O 2y O 2 The horizontal and vertical coordinates of the point;

[0111] O′ 1x , O′ 1y O′ 1 The horizontal and vertical coordinates of the point;

[0112] O′ 2x , O′ 2yO′ 1 The horizontal and vertical coordinates of the point;

[0113] According to the corrected coordinates of the transducer, the transducer position is adjusted.

[0114] In some embodiments, the yaw deviation is iteratively processed until two accurate models are obtained, where the accurate models are the most recently updated models of the final model, and the two accurate models correspond one-to-one to the two final models, including:

[0115] Define the water depth as H and the center of the precise model as A 1 The distance between point A and the final model is D 1 , accurate model center B 1 The distance between point and point B of the final model is D 2 , the termination condition of the iterative process is: D 1 <H×0.5% and D 2 <H×0.5%.

[0116] In order to verify the effectiveness of a method for detecting and correcting a bow roll deviation in a multi-beam bathymetry provided by an embodiment of the present invention, a set of simulation experiments was designed. In the experiment, ideal bathymetry data without a bow roll deviation was first used as a benchmark. Subsequently, a bow roll deviation was artificially introduced into these data to simulate the deviation that may occur in actual measurement. Specifically, the deviation value of the transducer was set to 10° to simulate the deviation that may occur during the installation or operation of the transducer in actual measurement.

[0117] After data processing, the generated simulation data is as follows Figure 3 As shown. It can be seen from the figure that the introduced bow roll deviation causes obvious rotational misalignment in the spatial distribution of the bathymetric data, which is consistent with the influence of the bow roll deviation on the data in actual measurement. Subsequently, the simulation data were processed using a multi-beam bathymetric bow roll deviation detection and correction method provided by an embodiment of the present invention. Through point cloud segmentation, cylinder fitting and bow roll deviation calculation based on geometric relationships, the final calculated bow roll deviation value is 9.91°. This result is very close to the artificially set transducer deviation value of 10°, with an error of only 0.09°, indicating that the method of the present invention can accurately detect the bow roll deviation in the bathymetric data.

[0118] After detecting the yaw deviation, the deviation value is further used as a correction term to adjust the position of the transducer, and the model is gradually optimized through iterative processing. After multiple iterative processes, the corrected terrain data is finally obtained, such as Figure 4 As shown. Figure 4It can be seen that the terrain data after the bow roll deviation correction has been restored to an ideal state close to no deviation, and the continuity and integrity of the terrain have been significantly improved. This result fully proves the effectiveness of the multi-beam bathymetric bow roll deviation detection and correction method provided by the embodiment of the present invention in a simulation environment.

[0119] In addition to the simulation experiments, actual measurement experiments were also conducted to verify the applicability and accuracy of the method of the present invention in actual measurement scenarios. In the actual measurement process, due to the combined effects of various factors such as the installation position of the transducer, the navigation attitude of the ship, and the marine environment, the transducer will inevitably have a certain installation deviation. This deviation will cause obvious bow deviation in the depth measurement data after processing, thereby affecting the accuracy and reliability of seabed topography mapping.

[0120] In order to verify the actual effect of the method of the present invention, a group of measured data with obvious bow roll deviation was selected for experiment. Figure 5 As shown in the figure, due to the influence of the bow roll deviation, the terrain data has obvious rotation dislocation in local areas, which not only affects the continuity of the terrain, but also may lead to deviations in subsequent marine engineering design and construction decisions.

[0121] The method for detecting and correcting the bow deviation of multi-beam bathymetric sounding provided in an embodiment of the present invention is used to detect the bow deviation of these measured data. After point cloud segmentation, cylinder fitting and geometric relationship calculation, the final detected bow deviation value is -7.43°. This result shows that there is indeed a significant bow deviation in the measured data, and the deviation direction is consistent with the actual measurement situation.

[0122] Subsequently, the position of the transducer is adjusted based on the detected yaw deviation value, and the terrain data is gradually corrected through iterative optimization processing. After multiple iterative processes, the corrected terrain data is obtained as follows Figure 6 As shown. Figure 6 It can be seen that the terrain data after the bow deviation correction has been restored to a relatively ideal state of continuity and integrity, and the local misalignment of the terrain has been significantly improved. This result fully proves the effectiveness and reliability of the multi-beam bathymetric bow deviation detection and correction method provided by the embodiment of the present invention in actual measurement scenarios.

[0123] In summary, the present invention provides a method for detecting and correcting the bow roll deviation in multi-beam bathymetry, which: 1. Realizes automated deviation detection: extracts target features and detects bow roll deviation through point cloud segmentation and cylinder fitting. 2. Improves measurement accuracy: iteratively optimizes the cylindrical model and processes the bow roll deviation twice to reduce the deviation error. 3. Simplifies the calculation process: simplifies the complex three-dimensional fitting problem into a two-dimensional linear fitting through coordinate transformation to reduce the calculation complexity. 4. Enhances applicability: It is suitable for offshore wind farms and other complex marine engineering scenarios, and can provide stable and high-precision measurements in dynamic environments.

[0124] Although the present invention has been disclosed as above with preferred embodiments, it is not intended to limit the present invention. A person with ordinary knowledge in the technical field to which the present invention belongs may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be determined by the definition of the claims.

Claims

1. A method for detecting and correcting multi-beam sounding bow deviation, characterized in that: include: S1. Obtain the normal vector of the wind power pile; S2. According to the normal vector of the wind turbine pile, the point cloud data of the wind turbine pile is segmented to obtain the wind turbine pile point cloud segmentation area 2 S3. Based on the shape of the wind turbine pile cylinder and the segmentation area of ​​the wind turbine pile point cloud, the final model of the wind turbine pile is obtained. S4. Calculating the yaw deviation according to the final model and the transducer data.

2. The method for detecting and correcting the multi-beam sounding heading deviation according to claim 1 is characterized in that: The step of performing point cloud segmentation on the wind power pile body point cloud data according to the wind power pile normal vector to obtain the wind power pile point cloud segmentation area includes: Select the seed point in the wind power pile point cloud data as the starting point; According to the normal vector of the wind turbine pile, the normal direction and curvature of the seed point and adjacent points are obtained: Compare the seed point and the adjacent points, and add the adjacent points with similar normal directions and similar curvatures to the wind power pile point cloud segmentation area; The point cloud data of the wind turbine pile body is processed iteratively until there are no points that meet the requirements of similar normal directions of the seed point and adjacent points and similar curvatures of the seed point and adjacent points, thus completing the point cloud segmentation.

3. The method for detecting and correcting the multi-beam sounding heading deviation according to claim 2 is characterized in that: The condition for the normal directions of the seed point and the adjacent points to be similar is that the angle between the normal vector of the seed point and the normal vector of the adjacent point is between [5°, 15°].

4. The method for detecting and correcting the multi-beam sounding bow deviation according to claim 2 is characterized in that: The condition for the curvature of the seed point and the adjacent points to be similar is that the curvature difference between the seed point and the adjacent points does not exceed 0.

01.

5. The method for detecting and correcting the multi-beam sounding heading deviation according to claim 1 is characterized in that: The method of obtaining the final model of the wind power pile based on the shape of the wind power pile cylinder and the wind power pile point cloud segmentation area includes: Performing coordinate transformation on the point cloud in the wind power pile point cloud segmentation area to obtain the wind power pile in a two-dimensional coordinate system, so that the axis of the wind power pile cylinder is parallel to the vertical direction in the coordinate system after the coordinate transformation, and the wind power pile cylinder is circular in the two-dimensional coordinate system; Establish an objective function based on the sum of squares of the distances from the point cloud points to the outer contour of the wind pile cylinder. Use the gradient descent algorithm to iteratively adjust the parameters of the wind pile cylinder model until the residual function used to quantify the total deviation between the point cloud points and the wind pile cylinder model converges. The model with the smallest error in the fitted wind turbine pile cylindrical model is taken as the final model, wherein the error refers to the distance from the point cloud point in the fitted wind turbine pile cylindrical model to the outer contour of the wind turbine pile cylinder.

6. The method for detecting and correcting the multi-beam sounding heading deviation according to claim 1 is characterized in that: The calculating the yaw deviation according to the final model and the transducer data comprises: Randomly select the final models of two wind power piles, and use the centers of the final models of the two wind power piles as point A and point B respectively; According to the final models of the two wind farms, the distances from each point on the final model to the corresponding transducer position at the launch time are calculated, and the transducer position with the smallest distance is taken as the rotation center, namely, point O1 and point O2; Calculate the lengths of O1A and O2B respectively; Assuming that point S is the true position of the geometric center of the wind turbine pile without the influence of pitch deviation, the coordinates of point S are calculated based on points A, B, O1, O2, O1A and O2B. The coordinate formula of point S is as follows: Among them, x A ,y A are the horizontal and vertical coordinates of point A; x B ,y B are the horizontal and vertical coordinates of point B; x s ,y s is the horizontal and vertical coordinates of point S; According to the coordinates of point O1, point A, and point S, calculate the lengths of the three sides of the triangle formed by point O1, point A, and point S, namely the lengths of O1A, O1S, and SA; According to the lengths of O1A, O1S and SA, the cosine value of the heading deviation is calculated using the following formula: According to the calculated cosine value of the heading deviation, the heading deviation is obtained through the inverse trigonometric function and the non-negativity of the heading deviation.

7. The method for detecting and correcting the multi-beam sounding heading deviation according to claim 6 is characterized in that: The method of obtaining the heading deviation according to the calculated cosine value of the heading deviation by using an inverse trigonometric function and the non-negativity of the heading deviation comprises: Taking the yaw deviation as a correction item; adjusting the position of the transducer according to the correction item; updating the final model according to the adjusted transducer position; The yaw deviation is iteratively processed until two accurate models are obtained, wherein the accurate models are the most recently updated models of the final model, and the two accurate models correspond one-to-one to the two final models.

8. The method for detecting and correcting the multi-beam sounding heading deviation according to claim 7 is characterized in that: According to the correction item, the position of the transducer is adjusted, including: Define the correction term as Δθ2 According to the correction item, the coordinates of the transducers corresponding to the points O1 and O2 are corrected to obtain the points o′1 and o′2. The correction formula is as follows: Among them, O 1x , O 1y are the horizontal and vertical coordinates of point O1; O 2x , O 2y are the horizontal and vertical coordinates of point O2; O′ 1x , O′ 1y are the horizontal and vertical coordinates of point O′1; O′ 2x , O′ 2y are the horizontal and vertical coordinates of point O′1; According to the corrected coordinates of the transducer, the transducer position is adjusted.

9. The method for detecting and correcting the multi-beam sounding heading deviation according to claim 7 is characterized in that: The iterative processing of the yaw deviation until two accurate models are obtained, wherein the accurate models are the most recently updated models of the final model, and the two accurate models correspond one-to-one to the two final models, comprises: Define the water depth as H, the distance between the center point A1 of the precise model and the point A of the final model as D1, the distance between the center point B1 of the precise model and the point B of the final model as D2, and the termination condition of the iterative process is: D1<H×0.5% and D2 <H×0.5%。

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