Multi-beam measurement-based sea area water taking channel scanning measurement method and system

Abstract

The invention relates to the technical field of underwater topographic surveying and mapping, in particular to a sea area water taking channel scanning survey method and system based on multi-beam measurement, and the method comprises the following steps: constructing a rigid support, fixing a depth finder through a three-way cable fastening device, and building a Boolean parameter model; sound velocity, tide level and original echo data are collected; performing space-time registration, coordinate conversion and filtering denoising on the data to generate corrected water depth; and constructing an irregular triangulation network by using hard boundary constraint, generating a digital elevation model, and extracting a siltation area. According to the invention, multi-beam wide sector scanning and multi-sensor attitude correction technologies are fused, a limited water area full-coverage measurement system is constructed, and the problems of terrain blind areas and detail loss are solved. A boundary constraint reconstruction algorithm is utilized to realize closed-loop processing from coordinate reference unification to micro-landform restoration, the accuracy of channel bottom pit capture and edge topography expression is improved, and data support is provided for sedimentation analysis.

Description

Technical Field

[0001] This invention relates to the field of underwater topographic mapping technology, and in particular to a method and system for scanning marine water intake channels based on multibeam bathymetry. Background Technology

[0002] The field of underwater topographic mapping technology involves the use of acoustic detection equipment to detect and image underwater bottom topography. Traditional methods for scanning water intake channels in marine areas primarily rely on single-beam echo sounders to acquire discrete depth point data. This point-to-line measurement mode involves vertical detection along a preset trajectory, resulting in numerous unsampled data gaps between the survey lines. Subsequent processing typically employs simple linear interpolation algorithms to simulate the overall topography, failing to accurately reflect the continuous morphology of complex underwater surfaces.

[0003] Traditional methods for surveying sea intake channels mainly rely on single-beam echo sounders to obtain discrete water depth data. This point-line measurement mode results in a large number of data gaps between survey lines. Due to the lack of full-coverage high-density point cloud support, simple linear interpolation alone cannot accurately restore the micro-topographic features of the channel bottom, and it is easy to miss key topographic changes such as deep pits or local siltation. At the same time, the single positioning mode is difficult to correct the attitude deviation of the hull under the impact of water flow in real time, causing point coordinate drift and elevation distortion, which seriously reduces the completeness and quantitative calculation accuracy of topographic monitoring in narrow and restricted waters. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and to propose a method and system for scanning and measuring marine water intake channels based on multibeam measurement.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for scanning marine water intake channels based on multibeam bathymetry, comprising the following steps:

[0006] S1: Construct a rigid support system on the side of the survey vessel, use a three-way cable fastening device to implement three-way tension locking of the multibeam echo sounder, select high-level control points for matching calculation, and construct the Bursa seven-parameter conversion model.

[0007] S2: Plan parallel survey lines along the water flow direction of the intake channel, control the multibeam echo sounder to perform acoustic scanning, obtain the ship attitude parameters through the positioning and attitude determination system, and generate original echo point cloud data by combining the sound velocity profile data collected by the sound velocity profiler and the real-time water level data collected by the tide meter.

[0008] S3: Perform spatiotemporal registration on the original echo point cloud data, call the Bursa seven-parameter transformation model to complete coordinate projection, use the ship attitude parameters, the sound speed profile data and the real-time water level data to perform sound path correction, remove abnormal floating noise points through the strip automatic filtering algorithm, and generate multi-maintenance corrected water depth data.

[0009] S4: Import the channel edge contour line and define it as a hard break line. Use the multi-maintenance positive water depth data to construct a boundary-constrained irregular triangular network model. Perform rasterization resampling to generate a high-resolution digital elevation model. Perform spatial overlay analysis based on the design bottom elevation surface to extract the siltation distribution area.

[0010] As a further aspect of the present invention, step S1 specifically comprises:

[0011] S11: Install a vertical steel pipe support on the side of the survey vessel, fix the transducer of the multibeam echo sounder to the bottom of the steel pipe, and set the three-way cable fastening device in the middle and upper part of the steel pipe. By applying pre-tension to the bow, stern and inner side of the ship respectively, the high-frequency vibration of the probe during dynamic navigation is suppressed.

[0012] S12: Select at least three national high-level control points around the survey area to set up benchmark stations, use the rover station to collect positioning data of the survey vessel under static and dynamic working conditions, calculate the correspondence between WGS84 coordinates and local construction coordinates through coordinate difference, and obtain the corresponding relationship dataset.

[0013] S13: Based on the corresponding dataset, establish the transformation equation of the spatial rectangular coordinate system, and use the least squares method to iteratively solve the transformation parameters containing three translation factors, three rotation angles and one scale ratio factor to generate the Bursa seven-parameter transformation model.

[0014] As a further aspect of the present invention, step S2 specifically includes:

[0015] S21: Based on the design width and design water depth of the water intake channel, plan the main survey line along the water flow direction and the inspection line perpendicular to the water flow direction, and set the overlap rate threshold of adjacent main survey lines so that the overlap of the acoustic coverage area between adjacent strips is not less than 20%.

[0016] S22: Trigger the multibeam echo sounder to emit a fan-shaped acoustic beam, record the intensity and propagation time of the echo signal in real time, use the synchronous trigger pulse signal to coordinate the positioning and attitude determination system, collect roll, pitch, heading and heave values ​​in real time, and generate ship attitude parameters.

[0017] S23: Control the sound velocity profiler to perform vertical deployment within the survey area, obtain sound wave propagation velocity values ​​at different water depth levels, and generate sound velocity profile data;

[0018] The vertical change in water level in the measurement area is continuously monitored using a tide gauge to generate real-time water level data;

[0019] S24: The propagation time, the ship attitude parameters, the sound speed profile data, and the real-time water level data are fused and correlated according to a unified GPS time reference to generate raw echo point cloud data.

[0020] As a further aspect of the present invention, step S3 specifically comprises:

[0021] S31: Calculate the time deviation between GNSS signal and sonar signal through positioning delay test, perform nanosecond-level time alignment on the original echo point cloud data, and use the Bursa seven-parameter transformation model to convert the geographic coordinates of the point cloud into engineering projection coordinates.

[0022] S32: Construct a layered sound velocity model based on the sound velocity profile data, correct the instantaneous pointing angle of the transducer by combining the ship attitude parameters, calculate the refraction path of the sound wave at the interface of each water layer using Snell's law, superimpose the real-time water level data to eliminate the tidal influence, and complete the three-dimensional spatial correction of the sound path.

[0023] S33: Start the strip automatic filtering algorithm, set a dynamic statistical window centered on the sounding point, calculate the average value and standard deviation of the point cloud depth within the window, and remove outlier noise points that exceed the preset information interval;

[0024] S34: Perform anisotropic weighted averaging on the filtered effective data to eliminate edge effects at strip splicing points and generate multi-dimensional corrected water depth data.

[0025] As a further aspect of the present invention, step S4 specifically comprises:

[0026] S41: Read the digital design drawings of the water intake canal, extract the outlines of the two sides of the top of the canal, define them as hard break lines, and restrict the terrain interpolation from crossing the physical boundary of the canal.

[0027] S42: Using the discrete measuring points in the multi-maintenance positive water depth data as vertices, construct an irregular triangular network according to the Deloni triangulation criterion, forcibly divide the side length of the triangle at the hard fracture line, and generate a boundary-constrained irregular triangular network model.

[0028] S43: Set the grid cell size according to the rules, and use the natural neighbor interpolation method to resample the boundary-constrained irregular triangular mesh model into a continuous grid matrix to generate a high-resolution digital elevation model.

[0029] S44: Obtain the design bottom elevation surface of the water intake channel, perform pixel-by-pixel difference calculation between it and the high-resolution digital elevation model, filter out areas where the elevation difference is greater than the preset siltation thickness threshold, and extract the siltation distribution area.

[0030] As a further aspect of the present invention, the specific execution process of sound path correction includes:

[0031] The initial grazing angle at the time of sound wave emission and the layer velocity of each layered medium are obtained. Based on the layered ray tracking algorithm, the horizontal displacement correction and vertical depth correction of the sound wave propagation in the water are calculated using the following formulas:

[0032] ;

[0033] and

[0034] ;

[0035] in, The total horizontal displacement correction representing the sound wave propagation path. The total vertical depth correction representing the sound wave propagation path. This represents the total number of water layers divided based on the aforementioned sound velocity profile data. Representing the The thickness of the water layer, Represents the sound wave at the 1st The angle of refraction in the water layer is obtained by recursively solving Snell's law based on the incident angle of the previous layer and the ratio of the sound speed between layers.

[0036] As a further aspect of the present invention, the specific execution process of spatial overlay analysis includes:

[0037] Obtain the measured elevation value of each grid cell in the high-resolution digital elevation model, and the design elevation value of the design bottom elevation surface at the corresponding location. Calculate the volume of silted soil within a single grid cell using the following formula:

[0038] ;

[0039] in, This represents the total volume of silted earth within the target area. This represents the total number of grid cells identified as siltation areas. Representing the The measured elevation value of each grid cell. Representing the Design elevation values ​​for each grid cell. Represents the projected area of ​​a single grid cell. This represents the volume correction factor that takes into account the gradient of the channel slope.

[0040] As a further aspect of the present invention, the construction process of the three-way cable fastening device specifically includes:

[0041] Weld the main fixing buckle to the inside of the hull of the survey vessel, and weld three radially distributed traction rings to the steel pipe support above the waterline.

[0042] The traction ring is connected to the mooring bollards at the bow and stern and the main fixing buckle by steel wire ropes respectively, and spiral turnbuckles are connected in series on each steel wire rope.

[0043] Tighten the turnbuckles in three directions alternately until the displacement of the steel pipe support relative to the hull when subjected to water flow impact is less than the preset micro-motion threshold, thus completing the rigid locking.

[0044] As a further aspect of the present invention, the specific execution process of the strip automatic filtering algorithm includes:

[0045] The original echo point cloud data is divided into several regular three-dimensional grid units, and the mean depth and depth error of all sounding points in each grid unit are calculated.

[0046] An estimation model based on combined uncertainty is constructed, and a confidence surface is generated for each grid cell according to the depth mean square error.

[0047] The vertical distance of each depth sounding point relative to the confidence surface is traversed and detected. If the vertical distance exceeds the preset confidence interval threshold, the depth sounding point is marked as floating noise and removed, and only valid depth points located within the confidence interval are retained.

[0048] A system for scanning marine water intake channels based on multibeam bathymetry, the system being used to implement the aforementioned method for scanning marine water intake channels based on multibeam bathymetry, the system comprising:

[0049] The support construction and parameter conversion module is used to construct a rigid support system on the side of the survey vessel and lock the multibeam echo sounder using a three-way cable fastening device. At the same time, it selects high-level control points to calculate the conversion relationship and generate the Bursa seven-parameter conversion model.

[0050] The multi-source data acquisition and scanning module is used to control the multibeam echo sounder to perform scanning along the planned survey line, and to synchronously acquire ship attitude parameters, sound velocity profile data and real-time water level data through various sensors to generate raw echo point cloud data.

[0051] The data registration and multi-dimensional correction module is used to perform spatiotemporal registration and coordinate projection on the original echo point cloud data, perform sound path correction based on sound speed and tide level, and purify the data through a strip automatic filtering algorithm to generate multi-dimensional corrected water depth data.

[0052] The model building and sedimentation analysis module is used to construct an irregular triangular mesh model with boundary constraints using hard fracture line constraints, resample to generate a high-resolution digital elevation model, and overlay and compare it with the design bottom elevation surface to extract the sedimentation distribution area.

[0053] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0054] This invention integrates multi-beam wide-sector scanning with high-precision multi-sensor attitude correction technology to construct a full-coverage three-dimensional measurement system for confined water areas. This effectively solves the problems of terrain blind spots and loss of details caused by traditional discrete measurements. By utilizing the Bursa seven-parameter model and the irregular triangular network reconstruction algorithm with boundary constraints, a closed-loop processing from coordinate benchmark unification to fine micro-topography restoration is achieved, significantly improving the accuracy of capturing deep pits at the bottom of the canal and expressing edge terrain. This high-precision digital modeling method provides accurate and reliable spatial data support for the quantitative analysis of siltation and dredging maintenance of marine water intake channels. Attached Figure Description

[0055] Figure 1 This is a flowchart of the marine water intake channel scanning method based on multibeam measurement according to the present invention;

[0056] Figure 2 This is a flowchart illustrating the rigid support construction and coordinate parameter transformation of the present invention.

[0057] Figure 3 This is a flowchart illustrating the original echo point cloud data acquisition and generation process of this invention.

[0058] Figure 4 This is a flowchart of the data spatiotemporal registration and acoustic correction processing of the present invention;

[0059] Figure 5 This is a flowchart of the extraction and analysis process for the sediment distribution area in this invention. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this invention clearer, the software-based technical solution is described in detail below with reference to system architecture diagrams and embodiments. It should be understood that the specific embodiments described herein are only for explaining the technical solutions of this invention and do not constitute a limitation on the scope of protection.

[0061] In the description of this invention, the system architecture relationships or data processing flows indicated by terms such as "layer," "module," "interface," "data flow," "client," and "server" are all defined based on the architecture diagram or flowchart corresponding to the embodiments. This way of describing is only used to clearly illustrate the logical relationships between the elements in the technical solution, and not to limit the physical deployment form. The term "multiple" includes two or more technical units, including but not limited to multiple data nodes, processing threads, service instances, or functional components and other scalable elements. The specific number is determined according to the actual business scenario and needs to be specifically specified.

[0062] Please see Figure 1 and Figure 2 This invention provides a technical solution: a method for scanning marine water intake channels based on multibeam bathymetry, comprising the following steps:

[0063] S1: Construct a rigid support system on the side of the survey vessel, use a three-way cable fastening device to implement three-way tension locking of the multibeam echo sounder, select high-level control points for matching calculation, and construct the Bursa seven-parameter conversion model.

[0064] Step S1 is as follows:

[0065] S11: Install a vertical steel pipe support on the side of the survey vessel, fix the transducer of the multibeam echo sounder to the bottom of the steel pipe, and set a three-way cable fastening device in the middle and upper part of the steel pipe. By applying pre-tension to the bow, stern and the inner side of the ship respectively, the high-frequency vibration of the probe during dynamic navigation is suppressed.

[0066] The construction process of the three-way cable fastening device specifically includes:

[0067] Weld the main fixing buckle to the inside of the hull of the survey vessel, and weld three radially distributed traction rings to the steel pipe support above the waterline.

[0068] The towing ring is connected to the mooring bollards at the bow and stern and the main fixing buckle by steel wire ropes respectively, and spiral turnbuckles are connected in series on each steel wire rope.

[0069] Tighten the turnbuckles alternately in three directions until the displacement of the steel pipe support relative to the hull when subjected to water flow impact is less than the preset micro-motion threshold, thus completing the rigid locking.

[0070] S12: Select at least three national high-level control points around the survey area to set up benchmark stations, use the rover station to collect positioning data of the survey vessel under static and dynamic working conditions, calculate the correspondence between WGS84 coordinates and local construction coordinates through coordinate difference, and obtain the corresponding dataset.

[0071] S13: Based on the correspondence dataset, establish the transformation equation of the spatial rectangular coordinate system, and use the least squares method to iteratively solve the transformation parameters containing three translation factors, three rotation angles and one scale ratio factor to generate the Bursa seven-parameter transformation model.

[0072] During the construction of a rigid support system on the hull of the survey vessel, ultrasonic non-destructive testing of the vessel's hull structure is first performed to ensure that the plate thickness meets welding and stress requirements. Subsequently, a three-way cable fastening device is used to implement three-way tension locking of the multibeam echo sounder. The installation point is selected at the edge of the deck one-third of the way from the bow on the starboard side of the survey vessel, using a seamless steel pipe with a diameter of 200 mm and a wall thickness of 10 mm as the main support material. A flange is welded to the bottom of the steel pipe to accommodate the installation interface of the multibeam transducer, and a streamlined flow guide is welded 30 cm above the flange to reduce the direct impact of water flow on the transducer. The multibeam echo sounder transducer is fixed to the bottom of the steel pipe with high-strength stainless steel bolts, and a data transmission cable is connected and led along the inner wall of the steel pipe to the control terminal on the deck. After the steel pipe is submerged, a three-way cable fastening device is used to apply pre-tension to the bow, stern, and inner side of the ship. This process requires precise control using a torque wrench and tension meter to ensure that the initial tension value in each direction reaches between 5,000 and 8,000 Newtons, thereby suppressing the high-frequency vibration of the probe during dynamic navigation.

[0073] When welding the main fixing buckle inside the hull of the survey vessel, the anti-rust paint and oxide layer on the hull surface must be removed. A carbon dioxide gas shielded welding process should be used, with a reinforcing rib plate having a base area of ​​no less than 200 square centimeters. A high-strength D-type shackle should then be welded at the center of the rib plate as the main fixing buckle. At a position 1.5 meters above the waterline of the steel pipe support, three radially distributed traction rings should be welded evenly along the circumference of the pipe wall, with the traction rings spaced at a 120-degree angle. A 6×19 galvanized steel wire rope with a diameter of 12 mm and a breaking strength of no less than 10 tons should be selected. The traction rings on the steel pipe should be connected to the mooring bollards at the bow and stern, and the main fixing buckle inside the hull, respectively, using the steel wire rope. An M24 spiral turnbuckle should be connected in series at the middle of each steel wire rope for subsequent tension fine-tuning. After the connection is completed, the operator needs to tighten the turnbuckles at both the bow and stern to keep the steel pipe vertical in the longitudinal direction, and then tighten the turnbuckles on the inside to make the steel pipe fit tightly against the anti-collision strip on the hull.

[0074] The process of alternately tightening the turnbuckles in three directions until rigid locking is achieved requires real-time vibration monitoring data. A triaxial accelerometer is installed at the bottom of the steel pipe support, with the sampling frequency set to 100Hz, to monitor the displacement of the support under water flow impact in real time. The measuring vessel's engine is started and its speed is increased from a stationary state to cruising conditions to simulate the water flow impact environment. Based on the feedback data from the accelerometer, the operator alternately adjusts the tightness of the three turnbuckles in 90-degree increments. When the monitoring system shows that the displacement of the steel pipe support relative to the hull along both the X-axis (lateral) and Y-axis (longitudinal) is less than 2 mm (i.e., the preset micro-motion threshold), the tightening operation is stopped, and the turnbuckles are locked with anti-loosening nuts to complete the rigid locking. Experimental data shows that at a speed of 6 knots, the transducer attitude jitter amplitude after this three-way locking is controlled within 0.05 degrees, meeting the requirements for high-precision scanning.

[0075] When setting up reference stations at at least three national high-level control points around the survey area, it is necessary to consult the surveying archives of the survey area and select known control points of level C or above. A dual-frequency GNSS receiver is set up at each control point as the reference station, with a sampling interval of 1 second and a satellite cutoff elevation angle of 15 degrees. Simultaneously, a GNSS receiver of the same model is installed on top of the rigid support of the survey vessel as a rover station. The rover station is used to collect positioning data of the survey vessel under static (stationary) and dynamic (navigating along an "8" shaped trajectory at 4 knots) conditions, with a collection time of no less than 1 hour. The observation data from the reference station and the rover station are imported into post-processing software. The precise three-dimensional coordinates of the rover station in the WGS84 coordinate system are calculated using carrier phase differential technology. Combined with the local construction coordinates of the known control points (such as an independent engineering coordinate system), the coordinate difference between the corresponding points in the two coordinate systems is calculated, thereby obtaining a dataset containing at least 10 sets of high-precision corresponding coordinate pairs.

[0076] When establishing transformation equations for a spatial rectangular coordinate system based on a correspondence dataset, a mathematical model incorporating translation, rotation, and scaling transformations is required. Coordinates in the WGS84 coordinate system are defined as source coordinates, and coordinates in the local construction coordinate system are defined as target coordinates. The Bursa-Wolf model is adopted, which assumes three-axis translations (DX, DY, DZ), three-axis rotations (RX, RY, RZ), and a scaling factor (K) between the two coordinate systems. The obtained corresponding coordinate pairs are substituted into the model to construct a set of error equations. Iterative solutions are performed using the least squares method, with an iteration convergence threshold of 1e-6 meters. Initially, the rotation angle is assumed to be 0, and the scaling factor is 1. Parameters are repeatedly adjusted until the unit weight error is less than the preset accuracy requirement (e.g., 1 cm). The seven parameters finally calculated constitute the Bursa seven-parameter transformation model. As shown in Table 1 below, high-precision transformation parameters were obtained by solving the measured data of a water intake canal project in a certain sea area, and the residual values ​​after transformation were all within the millimeter range, which verified the reliability of the model.

[0077] Table 1. Coordinate Transformation Parameters and Residual Verification Table

[0078]

[0079] The results show that after coordinate transformation using the seven-parameter model, the plane and elevation residuals of each verification point are controlled within 0.005 meters, which fully meets the stringent requirements of coordinate system transformation accuracy for precise surveying of water intake channels, and provides a solid mathematical foundation for accurate spatial positioning of subsequent point cloud data.

[0080] Please see Figure 1 and Figure 3 S2: Plan parallel survey lines along the water flow direction of the intake channel, control the multibeam echo sounder to perform acoustic scanning, obtain the ship attitude parameters through the positioning and attitude determination system, and generate raw echo point cloud data by combining the sound velocity profile data collected by the sound velocity profiler and the real-time water level data collected by the tide meter.

[0081] Step S2 is as follows:

[0082] S21: Based on the design width and design water depth of the water intake channel, plan the main survey line along the water flow direction and the inspection line perpendicular to the water flow direction, and set the overlap rate threshold of adjacent main survey lines so that the overlap of the acoustic coverage area between adjacent strips is not less than 20%.

[0083] S22: Triggers the multibeam echo sounder to emit a fan-shaped acoustic beam, records the intensity and propagation time of the echo signal in real time, and uses synchronous trigger pulse signals to coordinate the positioning and attitude determination system to collect roll, pitch, heading and heave values ​​in real time to generate ship attitude parameters.

[0084] S23: Control the sound velocity profiler to perform vertical deployment within the survey area, obtain sound wave propagation velocity values ​​at different water depth levels, and generate sound velocity profile data;

[0085] The vertical change in water level in the measurement area is continuously monitored using a tide gauge to generate real-time water level data.

[0086] S24: The propagation time, ship attitude parameters, sound velocity profile data and real-time water level data are fused and correlated according to a unified GPS time reference to generate raw echo point cloud data.

[0087] During the planning of parallel survey lines along the water flow direction of the intake canal, operators must first import the design CAD drawings of the intake canal into the navigation software and identify the central axis of the canal. Based on the design width of the intake canal (e.g., 50 meters) and the design water depth (e.g., 10 meters), combined with the effective opening angle of the multibeam echo sounder (set to 120 degrees), the effective coverage width of a single survey line is calculated. Based on the calculation results, the main survey lines are planned along the water flow direction, and the spacing between survey lines must ensure that the overlap of the acoustic coverage area between adjacent strips is not less than 20%. For example, when the effective coverage width of a single survey line is 34 meters, the spacing between survey lines should not exceed 27 meters. At the same time, a check line perpendicular to the water flow direction is planned every 500 meters for subsequent evaluation of the cross-accuracy of water depth measurement. When controlling the multibeam echo sounder to perform acoustic scanning, the power control unit on top of the sonar is turned on, and the operating frequency is set to 300kHz to balance depth resolution and range.

[0088] During real-time data acquisition, the transmitter of the multibeam echo sounder emits a fan-shaped acoustic beam towards the seabed under the control of a trigger pulse. The receiver simultaneously acquires the echo signal, recording its intensity and two-way propagation time via a built-in high-speed A / D converter. Simultaneously, the Positioning and Attitude System (POS) operates in high-frequency recording mode (200Hz), using two GPS antennas to determine the heading and an inertial measurement unit (IMU) to acquire real-time values ​​of the ship's roll, pitch, and heave under wave action. To ensure time synchronization of all sensors, all devices are connected to a 1PPS (pulse per second) signal generator, unifying the acoustic emission time and attitude acquisition time to microsecond-level accuracy, generating precise timestamps for the ship's attitude parameters.

[0089] When controlling the vertical deployment of the sound velocity profiler within the survey area, at least one deployment must be conducted before, during, and after the measurement, or an additional measurement must be performed immediately when the surface water temperature change exceeds 2 degrees Celsius. A portable sound velocity profiler (SVP) is used, lowered into the water at a constant speed via a winch, with the descent speed controlled within 1 m / s until it reaches the bottom of the channel. The instrument's built-in pressure, temperature, and conductivity sensors record data in real time, and the built-in algorithm calculates the sound wave propagation velocity values ​​at different water depth levels, with a sampling interval of 0.1 meters. The sound velocity profile data generated in this process will be used for subsequent sound wave refraction correction. Simultaneously, a radar-type tide gauge is installed in a still water area near the survey area, with a sampling interval of 1 minute, to continuously monitor the vertical change in water level in the survey area. The data is transmitted back to the survey vessel in real time via a GPRS network to generate real-time water level data, used to eliminate the influence of tides on water depth measurement.

[0090] When fusing and correlating propagation time, ship attitude parameters, sound velocity profile data, and real-time water level data, a post-processing matching strategy based on GPS time is employed. Since the data output frequencies of each sensor differ (50Hz for multibeam echolocation, 200Hz for POS, and 0.01Hz for tide gauge), the precise GPS time of multibeam echo emission is used as a reference. Linear interpolation is performed on the high-frequency attitude data to obtain the precise attitude at the moment of echo emission; spline function fitting is performed on the low-frequency water level data to obtain the instantaneous tide level value at that moment. All multi-source heterogeneous data matched by time index are packaged and stored to generate raw echo point cloud data containing spatial location, attitude information, and environmental parameters, with a data package size of approximately 2GB per hour. Experimental data shows that through this rigorous spatiotemporal synchronization mechanism, the positioning error caused by time delay during dynamic measurement is controlled within 5 cm.

[0091] Please see Figure 1 and Figure 4 S3: Perform spatiotemporal registration on the original echo point cloud data, call the Bursa seven-parameter transformation model to complete coordinate projection, use ship attitude parameters, sound speed profile data and real-time water level data to perform sound path correction, remove abnormal floating noise points through strip automatic filtering algorithm, and generate multi-maintained corrected water depth data.

[0092] The S3 steps are as follows:

[0093] S31: Calculate the time deviation between GNSS and sonar signals through positioning delay testing, perform nanosecond-level time alignment on the original echo point cloud data, and use the Bursa seven-parameter transformation model to convert the geographic coordinates of the point cloud into engineering projection coordinates.

[0094] S32: Construct a layered sound velocity model based on sound velocity profile data, correct the instantaneous pointing angle of the transducer by combining the ship's attitude parameters, calculate the refraction path of the sound wave at the interface of each water layer using Snell's law, superimpose real-time water level data to eliminate the tidal influence, and complete the three-dimensional spatial correction of the sound ray path.

[0095] The specific execution process of vocal path correction includes:

[0096] The initial grazing angle at the time of sound wave emission and the layer velocity of each layered medium are obtained. Based on the layered ray tracking algorithm, the horizontal displacement correction and vertical depth correction of the sound wave propagation in the water are calculated using the following formulas:

[0097] ;

[0098] and

[0099] ;

[0100] in, The total horizontal displacement correction representing the sound wave propagation path. The total vertical depth correction representing the sound wave propagation path. This represents the total number of water layers identified based on sound velocity profile data. Representing the The thickness of the water layer, Represents the sound wave at the 1st The angle of refraction in the water layer is obtained by recursively solving Snell's law based on the incident angle of the previous layer and the ratio of the sound speed between layers.

[0101] S33: Start the strip automatic filtering algorithm, set a dynamic statistical window centered on the sounding point, calculate the average and standard deviation of the point cloud depth within the window, and remove outliers that exceed the preset information interval.

[0102] The specific execution process of the strip automatic filtering algorithm includes:

[0103] The original echo point cloud data is divided into several regular 3D grid cells, and the mean depth and depth error of all sounding points in each grid cell are calculated.

[0104] An estimation model based on combined uncertainty is constructed, and a confidence surface is generated for each grid cell according to the depth mean square error.

[0105] The vertical distance of each sounding point relative to the confidence surface is traversed and detected. If the vertical distance exceeds the preset confidence interval threshold, the sounding point is marked as floating noise and removed. Only valid water depth points located within the confidence interval are retained.

[0106] S34: Perform anisotropic weighted averaging on the filtered effective data to eliminate edge effects at strip splicing points and generate multi-dimensional corrected water depth data.

[0107] When performing spatiotemporal registration on the raw echo point cloud data, installation deviation correction (PatchTest) is first required. By comparing forward and backward survey data for specific terrains (such as flat areas and sloping areas), the installation deviation angle (roll deviation, pitch deviation, and heading deviation) of the transducer relative to the inertial navigation unit is calculated. The time deviation between the GNSS signal and the sonar signal is calculated using a positioning delay test; this value is typically in the millisecond range. These calibration parameters are then applied to perform nanosecond-level time alignment on the raw echo point cloud data. Subsequently, the Bursa seven-parameter transformation model generated in step S1 is used to convert the latitude and longitude coordinates based on the WGS84 ellipsoid in the point cloud data point by point into the plane projection coordinates (such as Gauss-Kruger projection coordinates) and normal height system required for engineering, completing the mapping from geographic space to engineering space.

[0108] Constructing a layered sound velocity model based on sound velocity profile data is the core of sound path correction. The water body is vertically divided into several horizontal layers with relatively constant sound velocity gradients, for example, each layer is 1 meter thick. Combining the roll and pitch angles from the ship's attitude parameters, the instantaneous pointing angles of each transducer beam are corrected to obtain the initial incident angle of the sound wave on the transducer surface. Using Snell's Law, the refraction path of the sound wave as it passes through each medium interface is recursively calculated based on the sound velocity differences between the water layers. Real-time water level data is superimposed to normalize the initial depth of the sound wave to a depth reference surface (such as the theoretical lowest tide level).

[0109] The specific execution process of acoustic ray path correction involves complex geometric calculations. First, the initial grazing angle at the time of sound wave emission is obtained. and the layer velocity of each layered medium Based on the hierarchical sound ray tracking algorithm, the calculation is performed through the following logic: First, using data obtained from a sound velocity profiler, the ... Speed ​​of sound in a water layer With the The speed of sound in the layer The ratio, combined with the incident angle of the previous layer. Using Snell's Law The sound wave was calculated at the 1st... angle of refraction in the water layer Subsequently, the thickness of this water layer was obtained. (Determined by the depth of the sound velocity profile stratification). Substitute the above parameters into the following formula to calculate the horizontal displacement correction for sound wave propagation in water: And vertical depth correction: In the above calculations, This represents the total horizontal offset distance of the sound wave propagating from the transducer surface to the reflection point at the bottom of the lake / sea. This represents the total depth component of the sound wave propagation path in the vertical direction. This represents the total number of water layers that a sound wave traverses before reaching the lake / seabed. A practical example illustrates this: Assume the water depth at a measurement point is approximately 15 meters, and the sound velocity profile is divided into 15 layers, each 1 meter deep. The initial grazing angle of the sound wave is 45 degrees, the surface sound velocity is 1500 m / s, and the bottom sound velocity is 1480 m / s. The sound velocity at each layer... and thickness Substitute into the formula and calculate the angle of refraction layer by layer. The calculation results show that the uncorrected linear propagation model calculates a horizontal distance of 15.00 meters and a vertical depth of 15.00 meters; while the model corrected using the above formula... It is 14.85 meters. The depth was 14.98 meters. This result indicates that the sound ray bending effect caused a 0.15-meter deviation in horizontal position and a 0.02-meter deviation in vertical depth. Without this correction, the sounding point would be misaligned, severely affecting the modeling accuracy of the intake channel slope. The corrected coordinate data represents the true location of the underwater reflection point.

[0110] The strip automatic filtering algorithm is activated to remove abnormal suspended noise points. A circular region with a radius of 1 meter (i.e., twice the spot diameter) centered on an arbitrary sounding point is selected as a dynamic statistical window. The mean and standard deviation of the depth of all point clouds within the window are calculated. A confidence interval is constructed based on the 3σ criterion (3 times the standard deviation). Points with depth values ​​exceeding the range of [mean - 3 × standard deviation, mean + 3 × standard deviation] are considered noise points caused by fish, bubbles, or suspended debris and are removed. The specific execution process of the strip automatic filtering algorithm is further refined into CUBE (Combined Uncertainty and Bathymetry Estimator) type algorithm logic. The original echo point cloud data is divided into regular 3D grid cells with a size of 0.5 meters × 0.5 meters. The mean depth of all sounding points falling within each grid cell is calculated, and the depth mean error of the grid is calculated based on the sonar ranging uncertainty and attitude measurement error propagation model. An estimation model based on combined uncertainty is constructed, and a confidence surface representing the probability distribution of water depth is generated for each grid cell according to the depth mean square error. The vertical distance of each sounding point relative to the confidence surface is traversed and detected. If the vertical distance exceeds 0.3 meters (the preset confidence interval threshold), the sounding point is marked as floating noise and discarded, and only valid water depth points within the confidence interval are retained.

[0111] Anisotropic weighted averaging is performed on the filtered effective data. Since there are overlapping areas between adjacent survey lines, the data density in these areas is twice that of other areas, and there may be slight systematic biases. An inverse distance weighting (IDW) strategy is adopted, assigning weights based on the distance from the survey point to the grid center, with closer points receiving greater weights. Simultaneously, an incident angle weighting factor is introduced; points with smaller incident angles (closer to perpendicular incidence) have higher accuracy and are assigned greater weights. The final water depth value for each grid node is calculated through weighted averaging, thereby eliminating edge effects at strip junctions, smoothing data steps in overlapping areas, and generating continuous, smooth multi-level corrected water depth data.

[0112] Table 2 below shows a comparison of typical water depth data before and after acoustic correction and filtering:

[0113] Table 2 Comparison of Water Depth Data Correction and Filtering Effects

[0114] Please see Figure 1 and Figure 5 S4: Import the channel edge contour line and define it as a hard break line. Use multi-maintenance positive water depth data to construct a boundary-constrained irregular triangular network model. Perform rasterization resampling to generate a high-resolution digital elevation model. Perform spatial overlay analysis based on the design bottom elevation surface to extract the siltation distribution area.

[0115] The S4 steps are as follows:

[0116] S41: Read the digital design drawings of the water intake canal, extract the outlines of the two sides of the top of the canal, define them as hard break lines, and restrict the terrain interpolation from crossing the physical boundary of the canal.

[0117] S42: Using discrete measurement points in the multi-maintenance positive water depth data as vertices, an irregular triangular network is constructed following the Deloni triangulation criterion. The side lengths of the triangles are forcibly divided at hard fracture lines to generate a boundary-constrained irregular triangular network model.

[0118] S43: Set the grid cell size according to the rules, and use the natural neighbor interpolation method to resample the boundary-constrained irregular triangular mesh model into a continuous grid matrix to generate a high-resolution digital elevation model.

[0119] S44: Obtain the design bottom elevation surface of the water intake channel, perform pixel-by-pixel difference calculation between it and the high-resolution digital elevation model, filter out areas where the elevation difference is greater than the preset siltation thickness threshold, and extract the siltation distribution area.

[0120] The specific execution process of spatial overlay analysis includes:

[0121] Obtain the measured elevation value of each grid cell in the high-resolution digital elevation model, as well as the design elevation value of the design bottom elevation surface at the corresponding location, and calculate the volume of siltation within a single grid cell using the following formula:

[0122] ;

[0123] in, This represents the total volume of silted earth within the target area. This represents the total number of grid cells identified as siltation areas. Representing the The measured elevation value of each grid cell. Representing the Design elevation values ​​for each grid cell. Represents the projected area of ​​a single grid cell. This represents the volume correction factor that takes into account the gradient of the channel slope.

[0124] Importing the channel edge outline and defining it as a hard breakline is done in professional GIS or surveying software. First, the digital design drawings of the water intake channel (such as DWG or SHP format) are read, and the edge outlines on both sides of the channel top are extracted. These lines represent the physical boundary between man-made structures and natural terrain. These vector lines are imported into the software, and their attribute is defined as "Hard Breakline." This attribute setting restricts subsequent terrain interpolation algorithms from crossing this line for smoothing, thus maintaining the sharpness of the channel edges and accurately reflecting the geometric characteristics of the man-made channel.

[0125] A boundary-constrained triangular network (TIN) model is constructed using multi-maintenance corrected depth data. The software reads discrete measurement points from the multi-maintenance corrected depth data generated in step S3 as vertices. Following the Delaunay triangulation criterion—that "the circumcircle of any triangle cannot contain other data points"—the discrete points are connected into a network of non-overlapping triangles. In this process, rigid break lines play a crucial role; the algorithm forces the side lengths of the triangles to be aligned along the break lines, strictly prohibiting triangles from crossing them. In this way, the generated boundary-constrained TIN model can accurately represent the flatness of the channel floor and the steepness of the slopes, avoiding the "peak-shaving and valley-filling" distortion phenomenon that occurs in traditional TIN models at abrupt topographic changes.

[0126] A high-resolution digital elevation model (DEM) is generated through rasterization resampling. The grid cell size is set to 0.5 m × 0.5 m, a size that balances data storage capacity with detailed terrain representation. Natural Neighbor Interpolation is employed, a method that determines weights based on the area ratio of the Voronoi Diagrams surrounding the interpolation points. The boundary-constrained irregular triangular mesh model is resampled into a continuous raster matrix. Compared to linear interpolation, the natural neighbor method generates a smoother surface and better preserves local terrain features, ultimately producing a high-resolution DEM.

[0127] Spatial overlay analysis was performed based on the design bottom elevation surface to extract siltation distribution areas. First, the design bottom elevation surface data of the intake canal was obtained, which is typically a sloping plane or curved surface. Using the raster calculator function of GIS software, a pixel-by-pixel algebraic difference calculation was performed between the design bottom elevation surface and the measured high-resolution digital elevation model (measured elevation - design elevation). In the resulting matrix, positive values ​​represent siltation, and negative values ​​represent over-excavation. A siltation thickness threshold of 0.1 meters was set, and areas with an elevation difference greater than 0.1 meters were filtered out and rendered on the map using a specific color (e.g., red), thus visually extracting the siltation distribution areas.

[0128] The specific execution process of spatial overlay analysis includes the accurate calculation of earthwork volume and obtaining the measured elevation value of each raster cell in the high-resolution digital elevation model. And the design elevation value of the design bottom elevation surface at the corresponding location. Because the channel slopes have a certain angle of inclination, directly calculating the volume using the projected area will result in errors. Therefore, a volume correction factor needs to be introduced. The volume of silted soil within a single grid cell is calculated using the following formula: ;in, This represents the total volume of silted earth within the target area. It was identified as a silted-up area after screening (i.e.) The total number of grid cells (meters). The projected area representing a single grid cell is, in this embodiment, square meters. This represents the volume correction factor taking into account the gradient of the channel slope; for flat areas, it is set to 1.0; for sloping areas, the value is adjusted according to the slope. (For example, a 1:3 slope corresponds to approximately 18.4 degrees), its value is A practical example illustrates this: A 10-meter-long, 10-meter-wide section of a water intake channel is selected for calculation. This area contains 400 grid cells. Inspection revealed siltation in 250 of these cells. Assuming a typical grid cell has a measured elevation of -9.5 meters and a design elevation of -10.0 meters, the siltation thickness is 0.5 meters. This cell is located in a flat-bottomed area. The amount of sediment accumulation in this unit is... cubic meters. The total volume of silted earth in the area is obtained by summing up all 250 siltation units. Assuming a 100-meter-long section of the channel is calculated as a whole, the results are shown in Table 3 below. This result indicates that by introducing... The correction factor can more accurately invert the amount of siltation on the slope. Compared with the uncorrected vertical projection method, the accuracy of earthwork calculation is improved by about 3.5%, providing a more accurate bill of quantities for subsequent dredging projects.

[0129] Table 3. Calculation Results of Siltation Volume in Channel Sections

[0130]

[0131] A marine water intake canal scanning system based on multibeammetry is used to execute the aforementioned marine water intake canal scanning method based on multibeammetry. The system includes:

[0132] The support construction and parameter conversion module is used to construct a rigid support system on the side of the survey vessel and lock the multibeam echo sounder using a three-way cable fastening device. At the same time, it selects high-level control points to calculate the conversion relationship and generate the Bursa seven-parameter conversion model.

[0133] The multi-source data acquisition and scanning module is used to control the multibeam echo sounder to perform scanning along the planned survey line, and to synchronously acquire ship attitude parameters, sound velocity profile data and real-time water level data through various sensors to generate raw echo point cloud data.

[0134] The data registration and multi-dimensional correction module is used to perform spatiotemporal registration and coordinate projection on the raw echo point cloud data, perform sound path correction based on sound velocity and tidal level, and purify the data through a strip automatic filtering algorithm to generate multi-dimensional corrected water depth data.

[0135] The model building and sedimentation analysis module is used to construct an irregular triangular mesh model with boundary constraints using hard fracture line constraints, resample to generate a high-resolution digital elevation model, and overlay and compare it with the design bottom elevation surface to extract the sedimentation distribution area.

[0136] The above embodiments illustrate preferred embodiments of the present invention. Any equivalent adjustments to the technical solution based on software engineering methods are within the scope of protection, including but not limited to: implementing algorithm logic using different programming languages, refactoring functional modules into services, adjusting data interaction protocols, and optimizing resource scheduling strategies. Any implementation scheme derived from reasonable modifications to the data processing flow, service call chain, or system architecture layer without departing from the core technology of the present invention should be considered within the protection scope defined by the technical solution of the present invention.

Claims

1. A method for scanning marine water intake channels based on multibeam bathymetry, characterized in that, Includes the following steps: S1: Construct a rigid support system on the side of the survey vessel, use a three-way cable fastening device to implement three-way tension locking of the multibeam echo sounder, select high-level control points for matching calculation, and construct the Bursa seven-parameter conversion model. S2: Plan parallel survey lines along the water flow direction of the intake channel, control the multibeam echo sounder to perform acoustic scanning, obtain the ship attitude parameters through the positioning and attitude determination system, and generate original echo point cloud data by combining the sound velocity profile data collected by the sound velocity profiler and the real-time water level data collected by the tide meter. S3: Perform spatiotemporal registration on the original echo point cloud data, call the Bursa seven-parameter transformation model to complete coordinate projection, use the ship attitude parameters, the sound speed profile data and the real-time water level data to perform sound path correction, remove abnormal floating noise points through the strip automatic filtering algorithm, and generate multi-maintenance corrected water depth data. S4: Import the channel edge contour line and define it as a hard break line. Use the multi-maintenance positive water depth data to construct a boundary-constrained irregular triangular network model. Perform rasterization resampling to generate a high-resolution digital elevation model. Perform spatial overlay analysis based on the design bottom elevation surface to extract the siltation distribution area.

2. The method for scanning marine water intake channels based on multibeam bathymetry according to claim 1, characterized in that, The specific steps of S1 are as follows: S11: Install a vertical steel pipe support on the side of the survey vessel, fix the transducer of the multibeam echo sounder to the bottom of the steel pipe, and set the three-way cable fastening device in the middle and upper part of the steel pipe. By applying pre-tension to the bow, stern and inner side of the ship respectively, the high-frequency vibration of the probe during dynamic navigation is suppressed. S12: Select at least three national high-level control points around the survey area to set up benchmark stations, use the rover station to collect positioning data of the survey vessel under static and dynamic working conditions, calculate the correspondence between WGS84 coordinates and local construction coordinates through coordinate difference, and obtain the corresponding relationship dataset. S13: Based on the corresponding dataset, establish the transformation equation of the spatial rectangular coordinate system, and use the least squares method to iteratively solve the transformation parameters containing three translation factors, three rotation angles and one scale ratio factor to generate the Bursa seven-parameter transformation model.

3. The method for scanning marine water intake channels based on multibeam bathymetry according to claim 1, characterized in that, The specific steps of S2 are as follows: S21: Based on the design width and design water depth of the water intake channel, plan the main survey line along the water flow direction and the inspection line perpendicular to the water flow direction, and set the overlap rate threshold of adjacent main survey lines so that the overlap of the acoustic coverage area between adjacent strips is not less than 20%. S22: Trigger the multibeam echo sounder to emit a fan-shaped acoustic beam, record the intensity and propagation time of the echo signal in real time, use the synchronous trigger pulse signal to coordinate the positioning and attitude determination system, collect roll, pitch, heading and heave values ​​in real time, and generate ship attitude parameters. S23: Control the sound velocity profiler to perform vertical deployment within the survey area, obtain sound wave propagation velocity values ​​at different water depth levels, and generate sound velocity profile data; The vertical change in water level in the measurement area is continuously monitored using a tide gauge to generate real-time water level data; S24: The propagation time, the ship attitude parameters, the sound speed profile data, and the real-time water level data are fused and correlated according to a unified GPS time reference to generate raw echo point cloud data.

4. The method for scanning marine water intake channels based on multibeam measurement according to claim 1, characterized in that, The specific steps of S3 are as follows: S31: Calculate the time deviation between GNSS signal and sonar signal through positioning delay test, perform nanosecond-level time alignment on the original echo point cloud data, and use the Bursa seven-parameter transformation model to convert the geographic coordinates of the point cloud into engineering projection coordinates. S32: Construct a layered sound velocity model based on the sound velocity profile data, correct the instantaneous pointing angle of the transducer by combining the ship attitude parameters, calculate the refraction path of the sound wave at the interface of each water layer using Snell's law, superimpose the real-time water level data to eliminate the tidal influence, and complete the three-dimensional spatial correction of the sound path. S33: Start the strip automatic filtering algorithm, set a dynamic statistical window centered on the sounding point, calculate the average value and standard deviation of the point cloud depth within the window, and remove outlier noise points that exceed the preset information interval; S34: Perform anisotropic weighted averaging on the filtered effective data to eliminate edge effects at strip splicing points and generate multi-dimensional corrected water depth data.

5. The method for scanning marine water intake channels based on multibeam measurement according to claim 1, characterized in that, The specific steps of S4 are as follows: S41: Read the digital design drawings of the water intake canal, extract the outlines of the two sides of the top of the canal, define them as hard break lines, and restrict the terrain interpolation from crossing the physical boundary of the canal. S42: Using the discrete measuring points in the multi-maintenance positive water depth data as vertices, construct an irregular triangular network according to the Deloni triangulation criterion, forcibly divide the side length of the triangle at the hard fracture line, and generate a boundary-constrained irregular triangular network model. S43: Set the grid cell size according to the rules, and use the natural neighbor interpolation method to resample the boundary-constrained irregular triangular mesh model into a continuous grid matrix to generate a high-resolution digital elevation model. S44: Obtain the design bottom elevation surface of the water intake channel, perform pixel-by-pixel difference calculation between it and the high-resolution digital elevation model, filter out areas where the elevation difference is greater than the preset siltation thickness threshold, and extract the siltation distribution area.

6. The method for scanning marine water intake channels based on multibeam measurement according to claim 4, characterized in that, The specific execution process of the vocal path correction includes: The initial grazing angle at the time of sound wave emission and the layer velocity of each layered medium are obtained. Based on the layered ray tracking algorithm, the horizontal displacement correction and vertical depth correction of the sound wave propagation in the water are calculated using the following formulas: ； and ； in, The total horizontal displacement correction representing the sound wave propagation path. The total vertical depth correction representing the sound wave propagation path. This represents the total number of water layers divided based on the aforementioned sound velocity profile data. Representing the The thickness of the water layer, Represents the sound wave at the 1st The angle of refraction in the water layer is obtained by recursively solving Snell's law based on the incident angle of the previous layer and the ratio of the sound speed between layers.

7. The method for scanning marine water intake channels based on multibeam measurement according to claim 5, characterized in that, The specific execution process of the spatial overlay analysis includes: Obtain the measured elevation value of each grid cell in the high-resolution digital elevation model, and the design elevation value of the design bottom elevation surface at the corresponding location. Calculate the volume of silted soil within a single grid cell using the following formula: ； in, This represents the total volume of silted earth within the target area. This represents the total number of grid cells identified as siltation areas. Representing the The measured elevation value of each grid cell. Representing the Design elevation values ​​for each grid cell. Represents the projected area of ​​a single grid cell. This represents the volume correction factor that takes into account the gradient of the channel slope.

8. The method for scanning marine water intake channels based on multibeam measurement according to claim 2, characterized in that, The construction process of the three-way cable fastening device specifically includes: Weld the main fixing buckle to the inside of the hull of the survey vessel, and weld three radially distributed traction rings to the steel pipe support above the waterline. The traction ring is connected to the mooring bollards at the bow and stern and the main fixing buckle by steel wire ropes respectively, and spiral turnbuckles are connected in series on each steel wire rope. Tighten the turnbuckles in three directions alternately until the displacement of the steel pipe support relative to the hull when subjected to water flow impact is less than the preset micro-motion threshold, thus completing the rigid locking.

9. The method for scanning marine water intake channels based on multibeam measurement according to claim 4, characterized in that, The specific execution process of the strip automatic filtering algorithm includes: The original echo point cloud data is divided into several regular three-dimensional grid units, and the mean depth and depth error of all sounding points in each grid unit are calculated. An estimation model based on combined uncertainty is constructed, and a confidence surface is generated for each grid cell according to the depth mean square error. The vertical distance of each sounding point relative to the confidence surface is traversed and detected. If the vertical distance exceeds the preset confidence interval threshold, the sounding point is marked as floating noise and removed, and only valid water depth points located within the confidence interval are retained.

10. A marine water intake channel scanning system based on multibeam bathymetry, characterized in that, The system is used to implement the marine water intake channel scanning method based on multibeam measurement as described in any one of claims 1-9, and the system comprises: The support construction and parameter conversion module is used to construct a rigid support system on the side of the survey vessel and lock the multibeam echo sounder using a three-way cable fastening device. At the same time, it selects high-level control points to calculate the conversion relationship and generate the Bursa seven-parameter conversion model. The multi-source data acquisition and scanning module is used to control the multibeam echo sounder to perform scanning along the planned survey line, and to synchronously acquire ship attitude parameters, sound speed profile data and real-time water level data through various sensors to generate raw echo point cloud data. The data registration and multi-dimensional correction module is used to perform spatiotemporal registration and coordinate projection on the original echo point cloud data, perform sound path correction based on sound speed and tide level, and purify the data through a strip automatic filtering algorithm to generate multi-dimensional corrected water depth data. The model building and sedimentation analysis module is used to construct an irregular triangular mesh model with boundary constraints using hard fracture line constraints, resample to generate a high-resolution digital elevation model, and overlay and compare it with the design bottom elevation surface to extract the sedimentation distribution area.

Images