Underwater terrain inversion method for dredging process based on mass conservation and real-time positioning

Abstract

A method for inverting underwater terrain during a dredging process based on mass conservation and real-time positioning in the field of dredging technology includes the following steps: Step 1: measuring the initial terrain and water depth of the dredging area and performing grid division; Step 2: using a real-time dynamic positioning system to determine the horizontal coordinates of the dredging point, using a grid search algorithm to obtain the cell number where the dredging point is located, and using a ship-borne flowmeter to measure the mud flow in the dredging pipeline. The concentration is measured at the location of the mud suction port, and the concentration is measured using electrical resistance tomography technology based on an underwater electrode sensor array; Step 3: importing the horizontal coordinates of the dredging point, the cell number of the dredging point, the mud flow information of the dredging pipeline, and the mud concentration of the dredging pipeline into a data processing and imaging system, and using the mass conservation principle and a grid reconstruction algorithm to update the gridded terrain information and realize real-time inversion of the terrain. The present invention can realize real-time dynamic display of the terrain of the entire dredging area and is applicable to multi-vessel operations, thus solving the problem of real-time terrain inversion.

Description

Technical Field

[0001] The present invention relates to an underwater terrain inversion method in the field of dredging technology, in particular to an underwater terrain inversion method for a dredging process based on mass conservation and real-time positioning, which can realize real-time dynamic display of terrain in the entire dredging area. Background Art

[0002] With the development of dredging technology, higher requirements have been placed on excavation accuracy during the dredging process. To meet the excavation accuracy requirements, it is necessary to ensure the real-time and accuracy of topographic measurements. Currently, the common method for underwater topographic measurement is to use real-time dynamic positioning technology plus a digital depth sounder. Most of these measurements are pre-dredging and post-dredging measurements, making it difficult to measure topography during dredging projects. Real-time measurement of topography during dredging is of great significance for dredging accuracy control. Solving this problem is crucial for achieving high-precision dredging. This paper proposes a real-time inversion technology for topography during dredging. The equipment and instruments used are mostly commonly used instruments and equipment on dredging vessels, which is cost-effective and easy to use. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present invention proposes a method for underwater terrain inversion during the dredging process based on mass conservation and real-time positioning. The present invention is based on initial terrain measurement and real-time dynamic positioning technology, and utilizes the electrical resistance tomography technology based on an underwater sensor array to measure the concentration of the dredging vessel's onboard flow meter and the mud suction port. Based on the principle of mass conservation, underwater terrain inversion is performed, which can realize real-time dynamic display of the terrain of the entire dredging area and is suitable for multi-vessel operations.

[0004] The present invention is achieved through the following technical solutions: The present invention provides an underwater terrain inversion method for a dredging process based on mass conservation and real-time positioning, comprising the following steps: Step 1, measuring the initial terrain and water depth of the dredging area and gridding the initial terrain; Step 2, using a real-time dynamic positioning system to determine the horizontal coordinates of the dredging point, using a grid search algorithm to obtain the cell number where the dredging point is located, using a ship-borne flow meter to determine the mud flow in the dredging pipeline, and using electrical resistance tomography technology based on an underwater electrode sensor array to measure the mud concentration at the dredging pipeline suction port; Step 3, importing the horizontal coordinates of the dredging point, the cell number of the dredging point, the mud flow information of the dredging pipeline, and the mud concentration of the dredging pipeline into a data processing and imaging system, using the mass conservation principle and a grid reconstruction algorithm to update the gridded terrain information, and realizing real-time terrain inversion;

[0005] Among them, in step 1, the grid division of the initial terrain is to divide the initial terrain into a triangular grid or a quadrilateral grid, and the size of the cell is determined by the initial terrain accuracy and the real-time dynamic positioning accuracy; the number of divided cells is N, and the coordinates of the vertex of the i-th cell are P ij(x, y), unit is meter, j is the jth vertex of the i-th cell; if the mesh is a triangular mesh, then j = 1, 2, 3; if the mesh is a quadrilateral mesh, then j = 1, 2, 3, 4; the coordinates of the center point of the i-th cell are C i (x, y), unit is meter; water depth information is assigned to the center point of the grid, and the water depth of the i-th cell is H i , unit is meter; the area of ​​the i-th cell is S i , unit is square meter; the above values ​​are all known values ​​after the initial topographic survey and unit grid division are completed;

[0006] In step 2, the real-time dynamic positioning system is a GPS system and an angle sensor, and the horizontal coordinates of the dredging point measured by the real-time dynamic positioning system are P t (x,y), in meters.

[0007] Furthermore, in step 1 of the present invention, the water depth of the initial terrain of the dredging area is measured by a multi-beam bathymetric system.

[0008] Furthermore, in step 2 of the present invention, when the grid is triangular, the grid search algorithm steps for determining the number of dredging point cells are as follows:

[0009] Step 1: Calculate P t (x,y) and C i The absolute distance d between (x,y) i ;

[0010] Step 2: Find the cell k1 with the smallest d. The coordinates of the three vertices of the cell are calculate The angle values ​​of these 6 angles; if the sum of the angle values ​​of the 6 angles is 180°, then P t (x,y) is in cell k1; if the sum of the six angles is not 180°, proceed to step 3;

[0011] Step 3: Find the cell k2 with the smallest d value except k1, and then perform the same operation as step 2;

[0012] Step 4, and so on, finally find P t The number k of cells where (x,y) lies.

[0013] Furthermore, in step 2 of the present invention, the concentration measured by the electrical resistance tomography technology based on the underwater electrode sensor array is the concentration c at the pipeline suction port. vt .

[0014] Furthermore, in step 2 of the present invention, the mass conservation principle and the grid reconstruction algorithm are used to update the gridded terrain information, and the relevant calculation formula for achieving real-time inversion of the terrain is as follows:

[0015] According to the law of conservation of mass, the following relationship can be obtained:

[0016] Q t *Δt*c vt =S k *c0*Δh t

[0017] The calculation shows that the change in water depth at time t is:

[0018]

[0019] Reconstructing and updating the grid water depth yields:

[0020] H k t =H k t-1 +Δh t

[0021] where Q t is the slurry flow rate of the dredged pipeline at time t, in cubic meters per second; Δt is the measurement time interval, in seconds; c vt is the mud concentration at the dredging pipe suction port at time t, in percentage; S k is the area of ​​the kth cell, in square meters; c0 is the initial mud concentration of the in-situ sediment, in percentage; Δh t is the change in water depth at time t, in meters; H k t is the water depth value of the kth cell at time t, in meters; H k t-1 is the water depth value of the kth cell at time t-1, in meters; k t The calculation formula can obtain the grid water depth reconstruction value at any time and realize the real-time inversion of terrain.

[0022] Furthermore, in the present invention, the initial mud concentration c0 of the in-situ sediment is determined by on-site sampling.

[0023] Furthermore, in the present invention, the measurement time interval Δt is the least common multiple of the real-time dynamic positioning information update time interval, the flow meter sampling time interval, and the concentration meter sampling time interval.

[0024] Furthermore, in the present invention, when multiple ships are working simultaneously in the dredging area, data can be shared between the ships, and the shared data can be imported into their respective data processing and imaging systems to achieve terrain inversion imaging in the entire dredging area.

[0025] Furthermore, in step three of the present invention, the data processing and imaging system has the functions of excitation current signal output, sensor data reception and processing, and is implanted with grid search, grid water depth reconstruction algorithm and resistance tomography image reconstruction algorithm, which can complete data processing and calculation; it has the function of real-time imaging and can realize real-time imaging of inverted terrain.

[0026] Compared with existing technologies, this invention offers the following advantages: Based on initial topographic survey and real-time dynamic positioning technology, this invention utilizes electrical resistance tomography (ERT) technology based on an underwater sensor array, using a dredging vessel's onboard flowmeter and sludge suction port concentration measurement. Based on the principle of mass conservation, this invention proposes an underwater topographic inversion technique. This technique enables real-time dynamic topography display of the entire dredged area and is applicable to multi-vessel operations. Compared to traditional technologies, this method does not require real-time measurement using a shipboard digital depth sounder, reducing instrumentation, improving economic efficiency, and increasing convenience. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a schematic diagram of the underwater terrain inversion method for the dredging process based on mass conservation and real-time positioning of the present invention;

[0028] Figure 2 Schematic diagram of the structure of an embodiment of the present invention;

[0029] Figure 3 is a local grid map of the initial terrain in an embodiment of the present invention;

[0030] Numbers in the figure: 1. Dredging vessel, 2. Mud pump, 3. Flow meter, 4. Angle sensor, 5. Articulated device, 6. Mud suction pipe, 7. Mud suction device, 8. Initial topography, 9. Inverted topography, 10. Water surface, 11. Data processing and imaging system, 12. GPS device, 13. Sealed acquisition line, 14. Underwater electrode sensor array. DETAILED DESCRIPTION

[0031] The following describes an embodiment of the present invention in detail with reference to the accompanying drawings. This embodiment is based on the technical solution of the present invention and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiment.

[0032] Example

[0033] The present invention is as above Figure 1 and 2As shown, the present invention includes a dredging vessel 1, a mud pump 2, a flow meter 3, an angle sensor 4, an articulated device 5, a mud suction pipe 6, a mud suction device 7, an initial terrain 8, a water surface 10, a data processing and imaging system 11, a GPS device 12, a sealed acquisition line 13, and an underwater electrode sensor array 14. The dredging vessel 1 floats on the water surface 10, the mud pump 2, the data processing and imaging system 11, and the GPS device 12 are arranged on the dredging vessel 1, the mud suction device 7 is arranged on the initial terrain 8, one end of the mud suction pipe 6 is connected to the mud pump 2, and the other end of the mud suction pipe 5 is connected to the mud suction device 7, the flow meter 3 is arranged on the straight pipe section of the mud suction pipe 5, the angle sensor 4 is installed on the articulated device 5, and the underwater sensor array is installed near the mud suction port of the suction pipe 6. One end of the sealed acquisition line is connected to the underwater sensor array 14, and the other end is connected to the data processing and imaging system 11.

[0034] In the implementation process of the present invention, the depth of the initial terrain 8 is measured by a multi-beam bathymetry system; the initial terrain is divided into a triangular grid or a quadrilateral grid, and the size of the cell 17 is determined by the initial terrain accuracy and the real-time dynamic positioning accuracy. The number of divided cells is N, and the coordinates of the i-th cell vertex 15 are P ij (x, y), unit is meter, j is the jth vertex of the ith cell, if the mesh is a triangle mesh, then j = 1, 2, 3. If the mesh is a quadrilateral mesh, then j = 1, 2, 3, 4. The 16-bit coordinates of the center point of the ith cell are C i (x, y), unit is meter; water depth information is assigned to the center point of the grid, and the water depth of the i-th cell is H i , unit is meter; the area of ​​the i-th cell is S i , in square meters. The above values ​​are known after the initial topographic survey and unit grid division are completed.

[0035] Based on the natural settling of dredged in-situ sediment and assuming a uniform volume concentration, the initial concentration c0 of the in-situ sediment can be determined by field sampling. In this example, the initial concentration c0 is 50%.

[0036] Time information is processed in a discrete form. The positioning information update interval is Δt1, the flow meter sampling interval is Δt2, and the concentration sampling interval is Δt3. The terrain inversion interval is the lowest common multiple of these three values ​​of Δt, expressed in seconds. In this example, Δt is 0.1 seconds. The continuous time can then be discretized as t = m·Δt, where m is a positive integer.

[0037] The real-time dynamic positioning information of the mud suction device can be obtained by using GPS technology and angle sensor 4. The horizontal coordinate of the point is P t (x,y), in meters. Taking a triangular grid as an example, the grid search algorithm consists of the following steps:

[0038] First, calculate P t (x,y) and C i The absolute distance d between (x,y) i ;

[0039] Second, find the cell k1 with the smallest d, then the coordinates of the three vertices of the cell are calculate The angle values ​​of these 6 angles; if the sum of the angle values ​​of the 6 angles is 180°, then P t (x,y) is in cell k1. If the sum of the six angles is not 180°, proceed to step 3.

[0040] Third, find the cell k2 with the smallest d except k1, and then perform the same operation as step 2.

[0041] Fourth, and so on, we can finally find P t The number k of cells where (x,y) lies.

[0042] Using the grid search algorithm, we find that the dredging point is located in the 5th cell. The area of ​​the 5th cell is 1.0 square meters and the water depth is 2.30 meters.

[0043] If the mesh is a quadrilateral mesh, the steps are the same as the triangular mesh search algorithm. If P t When the sum of the eight angles formed by (x, y) and the four vertices of the cell is 360 degrees, P t (x,y) is inside the cell.

[0044] The measured mud concentration in the dredging pipeline is the mud suction port concentration. The underwater electrode sensor array 14 measures the boundary voltage value of the mud suction pipe when conveying clean water and mud. The mud suction port concentration c is measured by the image reconstruction algorithm embedded in the data processing and imaging system 11. vt , in percentage. Considering the continuity law of the fluid in the pipeline, there is no requirement for the installation position of flowmeter 3, and the measured flow rate Q t , in cubic meters per second. The transport concentration in this example is c vt It is 30% and the flow rate is 0.5 cubic meters per second.

[0045] Due to the randomness of mud diffusion during the dredging process, the mud inflow and mud outflow, i.e., the flux, for any unit grid is 0. Assuming that the sediment concentration after mud suspension and redeposition is equal to the initial concentration, the following relationship can be obtained according to the law of conservation of mass:

[0046] Q t *Δt*c vt =S k *c0*Δht (1)

[0047] It can be calculated that the change in water depth at time t is

[0048]

[0049] Reconstructing and updating the grid water depth yields:

[0050] H k t =H k t-1 +Δh t (3)

[0051] where Q t is the flow rate at time t, in cubic meters per second; Δt is the measurement time interval, in seconds; c vt is the mud delivery concentration in the mud suction pipe at time t, in percentage; S k is the area of ​​the kth cell, in square meters; c0 is the initial mud concentration, in percentage; Δh t is the change in water depth at time t, in meters; H k t is the water depth value of the kth cell at time t, in meters; H k t-1 is the water depth value of the kth cell at time t-1, in meters.

[0052] By using formula 3, the water depth reconstruction value of the 5th cell at 0.1 seconds can be obtained as 2.33 meters. Based on the above steps, the grid water depth reconstruction value at any time can be obtained to achieve real-time inversion of the terrain, such as Figure 2 Inverted topography 9.

[0053] In the present invention, the data processing and imaging system has data receiving and processing functions, is embedded with grid search and grid water depth reconstruction algorithms, and can complete data processing and calculation; it has real-time imaging functions and can realize real-time imaging of inverted terrain.

[0054] When multiple ships are working simultaneously in the dredging area, data can be shared between the ships, and the shared data can be imported into their respective data processing and imaging systems to achieve terrain inversion imaging in the entire dredging area.

[0055] The above describes the specific operation mode of the present invention. It should be understood that the present invention is not limited to the above specific operation mode, and those skilled in the art may make various variations or modifications within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. A method for underwater terrain inversion during dredging process based on mass conservation and real-time positioning, characterized in that: The following steps are involved: Step 1: Measure the initial topography and water depth of the dredging area and divide the initial topography into grids; Step 2: Use a real-time dynamic positioning system to determine the horizontal coordinates of the dredging point, use a grid search algorithm to obtain the cell number where the dredging point is located, use a ship-borne flow meter to measure the mud flow in the dredging pipeline, and use electrical resistance tomography technology based on an underwater electrode sensor array to measure the mud concentration at the dredging pipeline suction port; Step 3: Import the horizontal coordinates of the dredging points, the number of dredging point cells, the mud flow rate information of the dredging pipeline, and the mud concentration of the dredging pipeline suction port into the data processing and imaging system. Utilize the mass conservation principle and grid reconstruction algorithm to update the gridded terrain information and realize real-time inversion of the terrain. Among them, in step 1, the grid division of the initial terrain is to divide the initial terrain into a triangular grid or a quadrilateral grid, and the size of the cell is determined by the initial terrain accuracy and the real-time dynamic positioning accuracy; the number of divided cells is N, and the coordinates of the vertex of the i-th cell are P ij (x, y), unit is meter, j is the jth vertex of the i-th cell; if the mesh is a triangular mesh, then j = 1, 2, 3; if the mesh is a quadrilateral mesh, then j = 1, 2, 3, 4; the coordinates of the center point of the i-th cell are C i (x, y), unit is meter; water depth information is assigned to the center point of the grid, and the water depth of the i-th cell is H i , unit is meter; the area of ​​the i-th cell is S i , unit is square meter; the above values ​​are all known values ​​after the initial topographic survey and unit grid division are completed; In step 2, the real-time dynamic positioning system is a combination of a GPS system and an angle sensor. The horizontal coordinates of the dredging point measured by the real-time dynamic positioning system are P t (x,y), in meters; In step 3, the mass conservation principle and grid reconstruction algorithm are used to update the gridded terrain information, and the relevant calculation formula for achieving real-time inversion of the terrain is as follows: According to the law of conservation of mass, the following relationship can be obtained: Q t *Δt*c vt =S k *c0*Δh t The calculation shows that the change in water depth at time t is: Reconstructing and updating the grid water depth yields: H k t =H k t-1 +Δh t where Q t is the slurry flow rate of the dredged pipeline at time t, in cubic meters per second; Δt is the measurement time interval, in seconds; c vt is the mud concentration at the dredging pipe suction port at time t, in percentage; S k is the area of ​​the kth cell, in square meters; c0 is the initial mud concentration of the in-situ sediment, in percentage; Δh t is the change in water depth at time t, in meters; H k t is the water depth value of the kth cell at time t, in meters; H k t-1 is the water depth value of the kth cell at time t-1, in meters; k t The calculation formula can obtain the grid water depth reconstruction value at any time and realize the real-time inversion of terrain.

2. The underwater terrain inversion method for dredging process based on mass conservation and real-time positioning according to claim 1 is characterized in that In the step 1, the water depth of the initial terrain of the dredging area is measured by a multi-beam bathymetric system.

3. The underwater terrain inversion method for dredging process based on mass conservation and real-time positioning according to claim 1 is characterized in that In step 2, when the grid is triangular, the grid search algorithm steps for determining the number of dredging point cells are as follows: Step 1: Calculate P t (x,y) and C i The absolute distance d between (x,y) i ; Step 2: Find the cell k1 with the smallest d. The coordinates of the three vertices of the cell are calculate The angle values ​​of these 6 angles; if the sum of the angle values ​​of the 6 angles is 180°, then P t (x,y) is in cell k1; if the sum of the six angles is not 180°, proceed to step 3; Step 3: Find the cell k2 with the smallest d value except k1, and then perform the same operation as step 2; Step 4, and so on, finally find P t The number k of cells where (x,y) lies.

4. The underwater terrain inversion method for dredging process based on mass conservation and real-time positioning according to claim 1 is characterized in that The initial mud concentration c0 of the in-situ sediment is determined by on-site sampling.

5. The underwater terrain inversion method for dredging process based on mass conservation and real-time positioning according to claim 1 is characterized in that The measurement time interval Δt is the least common multiple of the real-time dynamic positioning information update time interval, the flow meter sampling time interval, and the concentration meter sampling time interval.

6. The underwater terrain inversion method for dredging process based on mass conservation and real-time positioning according to claim 1 is characterized in that When multiple ships are working simultaneously in the dredging area, data can be shared between the ships and the shared data can be imported into their respective data processing and imaging systems to achieve terrain inversion imaging in the entire dredging area.

7. The underwater terrain inversion method for dredging process based on mass conservation and real-time positioning according to claim 1 is characterized in that In step three, the data processing and imaging system has the functions of excitation current signal output, sensor data reception and processing, and is implanted with grid search, grid water depth reconstruction algorithm and resistance tomography image reconstruction algorithm, which can complete data processing and calculation; it has the function of real-time imaging and can realize real-time imaging of inverted terrain.

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