A high-precision underwater riprap method and system based on GPS positioning

Abstract

The present invention relates to the field of underwater riprap positioning technology, and in particular to a high-precision underwater riprap method and system based on GPS positioning. The method comprises the following steps: obtaining riprap deposition coordinate instructions; collecting riprap coordinates based on GPS technology and the riprap deposition coordinate instructions to obtain deposition coordinate data; establishing an initial underwater simulation topographic map; transmitting the deposition coordinate data to the initial underwater simulation topographic map for coordinate mapping to generate a simulated underwater topographic map; performing surface impact coordinate analysis of riprap according to the simulated underwater topographic map and the deposition coordinate data to generate surface impact coordinate data; designing a surface riprap delivery strategy according to the surface impact coordinate data; executing underwater riprap operations according to the surface riprap delivery strategy, and iteratively updating and optimizing the surface riprap delivery strategy. The present invention realizes a more accurate and efficient underwater riprap method.

Description

Technical Field

[0001] The present invention relates to the technical field of underwater riprap positioning, and in particular to a high-precision underwater riprap method and system based on GPS positioning. Background Art

[0002] Underwater riprap can help in related fields such as marine engineering, bridge construction and submarine pipeline laying. For example, it is used to build the foundation of breakwaters, ports and bridges. These structures often require a stable base to resist the erosion of ocean currents and waves, and riprap provides the stability of the base; and pipelines and cables laid on the seabed are often at risk of physical damage. Riprap can effectively provide them with a protective layer to prevent damage caused by external factors such as fishing gear and anchors. However, the traditional underwater riprap method relies on rough positioning technology and manual judgment, which has limitations in accuracy and efficiency, and does not consider the impact of hydrological data on riprap during the underwater riprap process, resulting in large deviations in the deposition process of underwater riprap, making the accuracy of underwater riprap poor. Summary of the invention

[0003] Based on this, the present invention provides a high-precision underwater riprap method and system based on GPS positioning to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a high-precision underwater riprap method based on GPS positioning includes the following steps:

[0005] Step S1: obtaining a riprap deposition coordinate instruction; collecting riprap coordinates based on GPS technology and the riprap deposition coordinate instruction to obtain deposition coordinate data;

[0006] Step S2: establishing an initial underwater simulated topographic map; transmitting the deposition coordinate data to the initial underwater simulated topographic map for coordinate mapping to generate a simulated underwater topographic map;

[0007] Step S3: performing a water surface impact coordinate analysis of the riprap according to the simulated underwater topographic map and the deposition coordinate data to generate water surface impact coordinate data;

[0008] Step S4: designing a surface riprap delivery strategy according to the surface impact coordinate data; performing underwater riprap operation according to the surface riprap delivery strategy, and collecting actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data; and iteratively updating and optimizing the surface riprap delivery strategy according to the actual deposition coordinate data.

[0009] The present invention collects riprap coordinates based on GPS technology and the riprap deposition coordinate instructions. The application of GPS technology can realize the positioning of the target position of riprap deposition in a complex underwater environment, ensure the accuracy and efficiency of the riprap operation, reduce the waste of riprap resources, and improve the quality of the entire underwater riprap project. Establishing an initial underwater simulation topographic map helps to better understand and predict the geographical features of the riprap area, including the slope, depth and other important topographic features of the seabed. Coordinate mapping using deposition coordinate data ensures high-precision matching of the riprap position, and the simulated underwater topographic map can also help analyze the possible sediment distribution after riprap. According to the simulated underwater topographic map and the deposition coordinate data, the water surface impact coordinate analysis of the riprap is performed. The precise analysis of the water surface impact point can ensure that the position of the riprap when it reaches the water surface is consistent with the expectation, thereby improving the accuracy of the entire deposition process, and helping to predict the behavior of the riprap in the water, including the sedimentation path and the final position, so as to optimize the riprap effect and ensure that the sediment is deposited according to the predetermined design. The riprap delivery strategy designed based on the water surface impact coordinate data can ensure that each riprap can reach the predetermined position more accurately, greatly improving the efficiency and accuracy of the operation. During the riprap operation, the actual deposition coordinate data is collected in real time, so that the placement strategy can be adjusted and optimized according to the actual situation. This dynamic adjustment mechanism can continuously improve the operation method and ensure the best riprap effect.

[0010] Preferably, step S1 comprises the following steps:

[0011] Get the command for riprap deposition coordinates;

[0012] Performing data analysis on the riprap deposition coordinate instruction to generate instruction analysis data, wherein the instruction analysis data includes riprap deposition area data and riprap deposition location data;

[0013] Underwater GPS mapping data of the riprap deposition area is collected by GPS technology;

[0014] The riprap coordinates are collected according to the riprap deposition positioning data and the underwater GPS surveying data to obtain deposition coordinate data.

[0015] The present invention performs detailed data analysis on the riprap deposition coordinate instructions, and the generated instruction analysis data includes the deposition area and positioning data, so as to collect the effective content in the instruction information and provide initial information for the target position of the riprap deposition. The use of GPS technology to collect underwater GPS mapping data of the deposition area ensures high-precision positioning of the riprap deposition area, which is crucial to ensure the precise landing point of the riprap. Accurate deposition area and positioning data make the entire riprap process more efficient and reduce erroneous operations caused by inaccurate positioning.

[0016] Preferably, step S2 comprises the following steps:

[0017] Step S21: designing an underwater simulation topographic map framework based on the underwater GPS surveying and mapping data;

[0018] Step S22: collecting underwater obstacle data of the underwater area corresponding to the underwater GPS mapping data based on the sonar equipment to generate underwater obstacle data;

[0019] Step S23: collecting hydrological information data for the underwater area corresponding to the underwater GPS surveying and mapping data to generate hydrological data;

[0020] Step S24: performing three-dimensional modeling of an initial underwater simulation topographic map based on the underwater simulation topographic map framework, underwater obstacle data, and hydrological data to establish an initial underwater simulation topographic map;

[0021] Step S25: transmitting the deposition coordinate data to the initial underwater simulation topographic map for coordinate mapping to generate a simulated underwater topographic map.

[0022] The present invention uses underwater GPS surveying data to design a simulation topographic map architecture, ensures the accuracy and reliability of the architecture, and provides a solid infrastructure to ensure the accuracy of subsequent simulation and analysis. Using sonar equipment to collect underwater obstacle data provides detailed information about underwater obstacles, and can accurately identify and record underwater obstacles, so as to avoid these obstacles in actual riprap operations and reduce risks and unnecessary interference. Collecting hydrological data of underwater areas, such as water flow direction, speed, etc., hydrological data is essential for understanding the underwater environment and helps to predict and simulate the behavior of riprap after deposition, such as the diffusion and stability of sediments. The three-dimensional simulation modeling is carried out by integrating the underwater simulation topographic map architecture, underwater obstacle data and hydrological data, providing a comprehensive and detailed view of the underwater environment, which helps to better understand and predict the impact of riprap and improve the accuracy and safety of the operation. Mapping the sedimentation coordinate data onto the initial underwater simulation topographic map to generate a simulated underwater topographic map with specific target information provides a visual guide that helps to further optimize the riprap strategy and improve the effect of the operation.

[0023] Preferably, step S3 comprises the following steps:

[0024] Step S31: performing data analysis of sedimentation deviation impact according to the simulated underwater topographic map to generate sedimentation deviation impact data;

[0025] Step S32: performing a deposition reverse path analysis according to the deposition coordinate data and the deposition deviation impact data to generate reverse deposition path data;

[0026] Step S33: performing reverse deposition path abnormality division processing on the reverse deposition path data according to the underwater obstacle data to obtain normal deposition path data and abnormal deposition path data;

[0027] Step S34: performing correction and adjustment processing on the abnormal deposition path data to generate corrected deposition path data;

[0028] Step S35: integrating the conventional deposition path data and the modified deposition path data to generate adjusted deposition path data;

[0029] Step S36: performing deposition coordinate adjustment processing on the deposition coordinate data according to the adjusted deposition path data to generate adjusted deposition coordinate data;

[0030] Step S37: performing water surface impact coordinate analysis of the riprap according to the adjusted deposition coordinate data and the adjusted deposition path data to generate water surface impact coordinate data.

[0031] The present invention performs data analysis based on a simulated underwater topographic map to identify factors that may affect the deposition position and generate deposition deviation influence data. This analysis helps to predict and identify factors that may cause sediments to deviate from the predetermined position, such as water flow, topography, etc., so as to make adjustments and plans in advance to reduce deviations. Reverse path analysis is performed using deposition coordinate data and deposition deviation influence data to generate reverse deposition path data. By analyzing the expected deposition path, the movement trajectory of sediments underwater is more accurately predicted, the stone throwing position and method are optimized, and the deposition effect is ensured to be consistent with expectations. Underwater obstacle data is used to analyze the reverse deposition path, and conventional and abnormal paths are distinguished. By identifying and processing abnormal paths, potential risks and obstacles can be prevented in advance, the deposition path can be optimized, and the safety and effectiveness of the operation can be ensured. The deposition path identified as abnormal is corrected and adjusted to generate corrected deposition path data. The corrected path data helps to reduce the potential risks and uncertainties caused by the abnormal path, ensure that the sediment is deposited according to the optimal path, and improve the reliability and efficiency of the operation. Conventional deposition path data and corrected deposition path data are comprehensively integrated to generate adjusted deposition path data, which ensures the integrity and consistency of the deposition path data and provides an accurate and comprehensive reference for the stone throwing operation. By integrating the data, the final position of the sediment can be better predicted and planned, ensuring the efficiency and accuracy of the riprap operation. Based on the adjusted sediment path data, the sediment coordinate data is precisely adjusted to generate the adjusted sediment coordinate data, further optimizing the accuracy of the sediment coordinates and ensuring that the sediment can reach the predetermined position more accurately. By adjusting the sediment coordinates, the repeated operations caused by deviation from the predetermined position can be reduced, and resource utilization and operation efficiency can be improved. The surface impact coordinates of riprap are analyzed using the adjusted sediment coordinate data and sediment path data to generate surface impact coordinate data, which can predict the impact position of the riprap on the water surface and provide key information for the actual riprap operation. Accurate surface impact coordinate data not only improves the accuracy of the riprap operation, but also helps to avoid potential risks and obstacles and ensure the safety of the operation.

[0032] Preferably, step S31 includes the following steps:

[0033] Collecting sedimentation depth data according to the simulated underwater topographic map and the sedimentation coordinate data to obtain sedimentation depth data;

[0034] Data analysis of sedimentation deviation impact is performed based on the sedimentation depth data and the hydrological data to generate sedimentation deviation impact data.

[0035] The present invention collects data on sediment depth based on simulated underwater topographic maps and sediment coordinate data to obtain information on the depth to which sediments may settle, and provides specific depth information that sediments may reach underwater, which is crucial for accurately predicting the final position of sediments. Accurate sediment depth data helps optimize the stone throwing strategy to ensure that sediments can effectively reach the predetermined position. Sediment depth data and hydrological data can be analyzed by fluid dynamics technology and other technologies to evaluate factors that may affect sediment deviation, such as water flow, hydrodynamic characteristics, etc. This analysis helps to understand and predict the behavior of sediments in underwater environments, especially in areas where fluid dynamics have a significant impact, to predict possible deviations of sediments, so as to make necessary adjustments and optimizations before actual stone throwing, reduce deviations, and ensure that sediments reach the predetermined position more accurately.

[0036] Preferably, step S34 includes the following steps:

[0037] Extracting abnormal riprap deposition nodes from the abnormal deposition path data to obtain abnormal deposition nodes;

[0038] Performing analysis and processing on traversable riprap deposition nodes according to the abnormal deposition nodes to generate traversable deposition nodes;

[0039] Performing a preferred feature node extraction process on the traversable deposition node to generate a traversable deposition feature node;

[0040] The number of abnormal deposition paths is corrected and adjusted according to the passable deposition feature nodes to generate corrected deposition path data.

[0041] The present invention extracts abnormal deposition nodes from abnormal deposition path data. These nodes are key points that cause the deposition path to deviate. Identifying these abnormal nodes helps to accurately locate the specific location that causes the deposition path to deviate, so that the correction process is more targeted, which is the premise for correcting the abnormal path and provides a basis for subsequent optimization. Analysis is performed based on abnormal deposition nodes to determine passable deposition nodes, thereby generating passable deposition nodes, which helps to distinguish those nodes that may become passable through adjustment, thereby optimizing the entire deposition path, reducing obstacles and risks in the deposition process, and ensuring the smooth deposition of sediments. Nodes with key or advantageous features are further extracted from the passable deposition nodes, which are called passable deposition feature nodes, such as the passable deposition nodes closest to the original nodes. By identifying these feature nodes, the deposition path is more effectively optimized, ensuring the efficiency and safety of the riprap deposition process. The extraction of feature nodes is a key step in achieving path optimization. Based on the passable deposition feature nodes, the abnormal deposition path data is corrected and adjusted to generate the corrected deposition path data, which can effectively correct the original abnormal path, reduce errors and risks in the deposition process, and ensure that the sediments arrive at the predetermined position smoothly according to the optimal path.

[0042] Preferably, step S4 comprises the following steps:

[0043] Step S41: designing a water surface riprap delivery strategy according to the water surface impact coordinate data;

[0044] Step S42: performing underwater riprap operation according to the surface riprap delivery strategy, and collecting actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data;

[0045] Step S43: performing deposition deviation distance calculation on the actual deposition coordinate data according to the adjusted deposition coordinate data to generate deposition deviation distance data of the actual deposition coordinate data;

[0046] Step S44: when the deposition deviation distance data is greater than a preset deposition deviation threshold, the surface riprap delivery strategy is iteratively updated and optimized.

[0047] The present invention designs a specific delivery strategy for surface riprap based on the surface impact coordinate data, ensuring that the initial strategy of the riprap operation can minimize the deposition deviation and improve the accuracy of the deposition. A reasonable delivery strategy is the basis for achieving efficient deposition, and significantly improves the efficiency and accuracy of underwater riprap operations. According to the designed delivery strategy, the actual underwater riprap operation is performed, and the actual coordinate data after deposition is collected. The collection of the actual deposition coordinate data is crucial for evaluating the effectiveness of the delivery strategy, ensuring that there is sufficient data support to analyze and optimize the delivery strategy. Based on the adjusted deposition coordinate data and the actual deposition coordinate data, the deposition deviation distance is calculated. The calculated deviation distance data provides direct feedback on the accuracy of the current delivery strategy, and is a key data indicator for evaluating and optimizing the strategy. When the deposition deviation distance exceeds the preset threshold, the delivery strategy is iteratively updated and optimized. This dynamic adjustment mechanism allows the delivery strategy to be continuously optimized according to the actual operation situation, ensuring the continuous improvement of the accuracy and efficiency of the deposition operation. This iterative update is the key to continuous improvement and adaptation to the ever-changing environment.

[0048] Preferably, step S44 includes the following steps:

[0049] When the deposition deviation distance data is greater than a preset deposition deviation threshold, the surface riprap delivery strategy corresponding to the deposition deviation distance data is marked as an abnormal riprap delivery strategy;

[0050] According to the preset intelligent tuning model, the abnormal riprap delivery strategy is optimized and adjusted to generate an optimized surface riprap delivery strategy;

[0051] The optimized surface riprap delivery strategy is fed back to the surface riprap delivery strategy of step S41 for iterative update and optimization.

[0052] In the present invention, when the sediment deviation distance data exceeds a preset threshold, the corresponding surface riprap delivery strategy is marked as abnormal, so that the delivery strategy that needs to be improved can be quickly identified, providing a clear goal for subsequent optimization. This is an important data self-assessment mechanism to ensure continuous monitoring and improvement of the accuracy of the delivery strategy. The delivery strategy marked as abnormal is optimized and adjusted using a preset intelligent tuning model to generate an optimized delivery strategy. The application of the intelligent tuning model makes the strategy optimization process more efficient and accurate. This data-driven optimization method can quickly respond to challenges in actual operations and improve the deposition accuracy of underwater riprap operations. The optimized delivery strategy is fed back to step S41 for iterative update and optimization. The iterative update mechanism ensures that the delivery strategy can continuously adapt to changes in actual operating conditions, thereby continuously improving the efficiency and accuracy of riprap operations, strengthening the learning and adaptability of the entire system, and providing motivation for continuous improvement and optimization of operating methods.

[0053] Preferably, the optimization and adjustment of the abnormal riprap strategy according to the preset intelligent tuning model includes the following steps:

[0054] Integrate the feedback data of abnormal riprap placement according to the abnormal riprap placement strategy to obtain abnormal riprap feedback data, wherein the abnormal riprap feedback data includes sedimentation deviation distance data and hydrological data corresponding to the abnormal riprap placement strategy;

[0055] Transmitting the abnormal riprap feedback data to a preset intelligent tuning model to perform optimization parameter prediction processing of the abnormal riprap delivery strategy to generate optimization parameters;

[0056] The abnormal riprap delivery strategy is optimized and adjusted according to the optimization parameters to generate an optimized surface riprap delivery strategy.

[0057] The present invention collects and integrates feedback data of abnormal rock dumping strategies, including sediment deviation distance data and hydrological data related to the strategy, and provides a comprehensive data view, which helps to deeply understand the specific factors that cause the strategy abnormality. The integrated data provides necessary input for the intelligent model, increasing the accuracy and effectiveness of optimization. The abnormal rock dumping feedback data is input into the preset intelligent tuning model to predict the optimization parameters of the strategy. The intelligent model can predict the optimal adjustment parameters based on actual data. This data-driven prediction improves the accuracy and efficiency of optimization. The application of the model can quickly identify the most effective adjustment strategy and reduce trial and error time. According to the optimization parameters predicted by the intelligent model, the abnormal rock dumping strategy is adjusted to generate an optimized strategy, so that the delivery strategy can be accurately adjusted according to the actual operation feedback, improving the accuracy and adaptability of the operation. Through optimization and adjustment, the strategy becomes more flexible and effective to cope with complex and changeable underwater environments.

[0058] This specification provides a high-precision underwater riprap system based on GPS positioning, which is used to execute the high-precision underwater riprap method based on GPS positioning as described above. The high-precision underwater riprap system based on GPS positioning includes:

[0059] A deposition coordinate data acquisition module is used to obtain riprap deposition coordinate instructions; based on GPS technology and the riprap deposition coordinate instructions, riprap coordinates are collected to obtain deposition coordinate data;

[0060] A simulated underwater topographic map establishment module is used to establish an initial underwater simulated topographic map; the deposition coordinate data is transmitted to the initial underwater simulated topographic map for coordinate mapping to generate a simulated underwater topographic map;

[0061] A water surface impact coordinate data analysis module, used for performing water surface impact coordinate analysis of riprap according to the simulated underwater topographic map and the deposition coordinate data to generate water surface impact coordinate data;

[0062] The underwater riprap operation module is used to design a surface riprap delivery strategy according to the surface impact coordinate data; perform underwater riprap operation according to the surface riprap delivery strategy, and collect actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data; and iteratively update and optimize the surface riprap delivery strategy according to the actual deposition coordinate data.

[0063] The beneficial effect of the present application is that the high-precision underwater riprap method based on GPS positioning of the present invention relies on accurate GPS positioning technology and simulated riprap simulation technology, and can more accurately find the target deposition position of underwater riprap and the simulated deposition path existing in underwater riprap, so that the accuracy and efficiency of underwater riprap are higher, and the influence of hydrological data on riprap during underwater riprap can be considered, and then the data parameters in the underwater riprap process can be continuously iterated and optimized, so that the accuracy of underwater riprap is higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A schematic diagram of the steps of a high-precision underwater riprap method based on GPS positioning according to the present invention;

[0065] Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart;

[0066] Figure 3 for Figure 1 Detailed implementation steps of step S3 in FIG.

[0067] Figure 4 for Figure 1 Detailed implementation steps of step S4 in FIG.

[0068] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0069] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0070] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0071] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0072] To achieve this, please refer to Figures 1 to 4 The present invention provides a high-precision underwater riprap method based on GPS positioning, comprising the following steps:

[0073] Step S1: obtaining a riprap deposition coordinate instruction; collecting riprap coordinates based on GPS technology and the riprap deposition coordinate instruction to obtain deposition coordinate data;

[0074] Step S2: establishing an initial underwater simulated topographic map; transmitting the deposition coordinate data to the initial underwater simulated topographic map for coordinate mapping to generate a simulated underwater topographic map;

[0075] Step S3: performing a water surface impact coordinate analysis of the riprap according to the simulated underwater topographic map and the deposition coordinate data to generate water surface impact coordinate data;

[0076] Step S4: designing a surface riprap delivery strategy according to the surface impact coordinate data; performing underwater riprap operation according to the surface riprap delivery strategy, and collecting actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data; and iteratively updating and optimizing the surface riprap delivery strategy according to the actual deposition coordinate data.

[0077] The present invention collects riprap coordinates based on GPS technology and the riprap deposition coordinate instructions. The application of GPS technology can realize the positioning of the target position of riprap deposition in a complex underwater environment, ensure the accuracy and efficiency of the riprap operation, reduce the waste of riprap resources, and improve the quality of the entire underwater riprap project. Establishing an initial underwater simulation topographic map helps to better understand and predict the geographical features of the riprap area, including the slope, depth and other important topographic features of the seabed. Coordinate mapping using deposition coordinate data ensures high-precision matching of the riprap position, and the simulated underwater topographic map can also help analyze the possible sediment distribution after riprap. According to the simulated underwater topographic map and the deposition coordinate data, the water surface impact coordinate analysis of the riprap is performed. The precise analysis of the water surface impact point can ensure that the position of the riprap when it reaches the water surface is consistent with the expectation, thereby improving the accuracy of the entire deposition process, and helping to predict the behavior of the riprap in the water, including the sedimentation path and the final position, so as to optimize the riprap effect and ensure that the sediment is deposited according to the predetermined design. The riprap delivery strategy designed based on the water surface impact coordinate data can ensure that each riprap can reach the predetermined position more accurately, greatly improving the efficiency and accuracy of the operation. During the riprap operation, the actual deposition coordinate data is collected in real time, so that the placement strategy can be adjusted and optimized according to the actual situation. This dynamic adjustment mechanism can continuously improve the operation method and ensure the best riprap effect.

[0078] In the embodiment of the present invention, reference Figure 1 The above is a schematic diagram of the steps of an intelligent medication management method of the present invention. In this embodiment, the intelligent medication management method includes the following steps:

[0079] The present invention provides a high-precision underwater riprap method based on GPS positioning, comprising the following steps:

[0080] Step S1: obtaining a riprap deposition coordinate instruction; collecting riprap coordinates based on GPS technology and the riprap deposition coordinate instruction to obtain deposition coordinate data;

[0081] In an embodiment of the present invention, the rock dumping deposition coordinate instructions are obtained from the control center or the underwater rock dumping operation plan. These instructions generally include the latitude and longitude coordinates of the predetermined rock dumping location, for example: "35.1234 degrees north latitude, 120.5678 degrees east longitude", as well as the predetermined rock dumping depth and time. A high-precision GPS receiver is used for coordinate acquisition. The GPS receiver on the device accurately locates the predetermined rock dumping area through satellite signals and records specific coordinate data. For example, the GPS device can be set to record position data every 10 seconds to ensure accurate tracking of the rock dumping location. In addition, advanced GPS technology such as differential GPS (DGPS) can be used to improve the accuracy of positioning and reduce the positioning error to the centimeter level. The collected data will be stored in a digital format, for example: "the actual rock dumping point is 35.12345 degrees north latitude, 120.56789 degrees east longitude" to obtain the deposition coordinate data and transmit it back to the control center.

[0082] Step S2: establishing an initial underwater simulated topographic map; transmitting the deposition coordinate data to the initial underwater simulated topographic map for coordinate mapping to generate a simulated underwater topographic map;

[0083] In an embodiment of the present invention, underwater terrain data of the target area is collected, which can be performed by multi-beam sonar, side-scan sonar or underwater unmanned aerial vehicle (ROV) and other technologies. For example, a multi-beam sonar is used to scan the predetermined area to collect information such as the depth, slope, and bottom quality of the terrain. These data are used to build a detailed three-dimensional underwater terrain model, such as using professional software such as ArcGIS or QGIS to process and visualize these data. Next, the sedimentary coordinate data collected by GPS technology is integrated into this initial terrain map. For example, if the GPS data shows that the predetermined riprap point is 35.12345 degrees north latitude and 120.56789 degrees east longitude, this coordinate point will be accurately marked on the underwater terrain model, involving the conversion and calibration of the coordinate system to ensure the accurate correspondence between the terrain data and the GPS data. The GPS coordinate data and the underwater terrain data are integrated to generate a comprehensive simulated underwater terrain map, which not only shows the underwater terrain features, but also accurately marks the predetermined riprap point. For example, riprap sites can be marked on a topographic map with different colors or symbols, while also showing details of the surrounding terrain, such as gullies, rocks, or other obstacles.

[0084] Step S3: performing a water surface impact coordinate analysis of the riprap according to the simulated underwater topographic map and the deposition coordinate data to generate water surface impact coordinate data;

[0085] In the embodiment of the present invention, the surface impact coordinates of the riprap are analyzed based on the generated simulated underwater topographic map and deposition coordinate data. First, the simulated underwater topographic map and deposition coordinate data are loaded using simulation software (such as MATLAB or professional marine engineering simulation software). Then, the physical model is used to simulate the process of the riprap falling from the water surface to the deposition point, taking into account the size, shape, weight of the riprap, and the influence of water flow, water depth and other environmental factors on the trajectory of the riprap. For example, assuming that the deposition coordinates are 35.12345 degrees north latitude, 120.56789 degrees east longitude, and 30 meters deep, an imaginary drop point is set on the water surface above this coordinate point, and then the falling trajectory of the riprap is simulated according to the physical properties of the riprap (such as 1 meter in diameter and 200 kilograms in weight) and environmental conditions (such as water flow speed and direction). The complete trajectory of the riprap from the water surface contact point to the deposition point will be calculated, and the specific position where the riprap contacts the water surface will be specially marked, that is, the surface impact coordinate, which may be different from the initial deposition coordinate due to factors such as water flow. For example, the simulation results may show that the actual water surface impact coordinates are 35.12350 degrees north latitude and 120.56785 degrees east longitude. Finally, these water surface impact coordinate data are recorded for the subsequent design of the water surface riprap delivery strategy.

[0086] Step S4: designing a surface riprap delivery strategy according to the surface impact coordinate data; performing underwater riprap operation according to the surface riprap delivery strategy, and collecting actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data; and iteratively updating and optimizing the surface riprap delivery strategy according to the actual deposition coordinate data.

[0087] In an embodiment of the present invention, a surface riprap strategy is designed based on the previously obtained surface impact coordinate data. Assume that the surface impact coordinate data shows that the predetermined impact point is 35.12350 degrees north latitude and 120.56785 degrees east longitude. Considering the influence of water flow and other environmental factors, the position of the actual riprap point needs to be adjusted to ensure that the stone is finally accurately deposited at the target coordinate point. Use professional marine engineering software, such as HydroCAD, to design a surface riprap strategy, including calculating the optimal riprap angle, speed and timing, and considering how to use ships or other equipment to implement this strategy. For example, we may decide to rip rocks from a position 35.12355 degrees north latitude and 120.56780 degrees east longitude from the predetermined impact point to compensate for the displacement caused by the water flow and perform underwater riprap operations. In operation, a device equipped with a GPS and a depth sensor is used to accurately record the actual deposition coordinate data, and it may be found that the actual deposition coordinates are 35.12348 degrees north latitude and 120.56783 degrees east longitude. Iteratively updating and optimizing the surface riprap strategy based on these actual deposition coordinate data involves analyzing the deviation between the actual deposition point and the predetermined point, and adjusting the riprap strategy to reduce this deviation. For example, if the actual deposition point is found to systematically deviate from the predetermined point, it may be necessary to adjust the riprap angle or consider riprap at different times to adapt to tidal changes.

[0088] Preferably, step S1 comprises the following steps:

[0089] Get the command for riprap deposition coordinates;

[0090] Performing data analysis on the riprap deposition coordinate instruction to generate instruction analysis data, wherein the instruction analysis data includes riprap deposition area data and riprap deposition location data;

[0091] Underwater GPS mapping data of the riprap deposition area is collected by GPS technology;

[0092] The riprap coordinates are collected according to the riprap deposition positioning data and the underwater GPS surveying data to obtain deposition coordinate data.

[0093] The present invention performs detailed data analysis on the riprap deposition coordinate instructions, and the generated instruction analysis data includes the deposition area and positioning data, so as to collect the effective content in the instruction information and provide initial information for the target position of the riprap deposition. The use of GPS technology to collect underwater GPS mapping data of the deposition area ensures high-precision positioning of the riprap deposition area, which is crucial to ensure the precise landing point of the riprap. Accurate deposition area and positioning data make the entire riprap process more efficient and reduce erroneous operations caused by inaccurate positioning.

[0094] In an embodiment of the present invention, riprap deposition coordinate instructions are obtained from a control center or an underwater riprap operation plan. These instructions are usually provided in the form of electronic documents or data transmissions, and contain detailed information about the riprap deposition area and specific positioning. For example, the instructions may specify that in a marine engineering area, the specific location is 35.12345 degrees north latitude and 120.5678 degrees east longitude, and riprap deposition needs to be carried out at a water depth of 30 meters. These instructions are data parsed to generate instruction parsing data. This process can be automatically completed by professional software, in which the riprap deposition area data indicates the approximate area of ​​the riprap operation, and the riprap deposition positioning data provides accurate GPS coordinates. For example, the parsed data may show that the riprap area is a circular area with a radius of 500 meters, and the center coordinates are the specific location given in the instruction. Use a ship or drone equipped with a GPS device to conduct underwater GPS mapping in the designated riprap deposition area, including detailed measurements throughout the area to collect detailed underwater terrain and environmental data. For example, the ship may navigate in the area at a predetermined path and interval, and record GPS position and water depth data every certain distance. The riprap coordinates are collected based on the riprap deposition positioning data and the collected underwater GPS mapping data. The best riprap coordinates are determined by comprehensive analysis of the positioning data and mapping data. For example, based on the analysis of the mapping data, the most suitable coordinates for riprap may be fine-tuned to ensure that the riprap can accurately reach the predetermined deposition point, taking into account the influence of water flow and terrain.

[0095] Preferably, step S2 comprises the following steps:

[0096] Step S21: designing an underwater simulation topographic map framework based on the underwater GPS surveying and mapping data;

[0097] Step S22: collecting underwater obstacle data of the underwater area corresponding to the underwater GPS mapping data based on the sonar equipment to generate underwater obstacle data;

[0098] Step S23: collecting hydrological information data for the underwater area corresponding to the underwater GPS surveying and mapping data to generate hydrological data;

[0099] Step S24: performing three-dimensional modeling of an initial underwater simulation topographic map based on the underwater simulation topographic map framework, underwater obstacle data, and hydrological data to establish an initial underwater simulation topographic map;

[0100] Step S25: transmitting the deposition coordinate data to the initial underwater simulation topographic map for coordinate mapping to generate a simulated underwater topographic map.

[0101] The present invention uses underwater GPS surveying data to design a simulation topographic map architecture, ensures the accuracy and reliability of the architecture, and provides a solid infrastructure to ensure the accuracy of subsequent simulation and analysis. Using sonar equipment to collect underwater obstacle data provides detailed information about underwater obstacles, and can accurately identify and record underwater obstacles, so as to avoid these obstacles in actual riprap operations and reduce risks and unnecessary interference. Collecting hydrological data of underwater areas, such as water flow direction, speed, etc., hydrological data is essential for understanding the underwater environment and helps to predict and simulate the behavior of riprap after deposition, such as the diffusion and stability of sediments. The three-dimensional simulation modeling is carried out by integrating the underwater simulation topographic map architecture, underwater obstacle data and hydrological data, providing a comprehensive and detailed view of the underwater environment, which helps to better understand and predict the impact of riprap and improve the accuracy and safety of the operation. Mapping the sedimentation coordinate data onto the initial underwater simulation topographic map to generate a simulated underwater topographic map with specific target information provides a visual guide that helps to further optimize the riprap strategy and improve the effect of the operation.

[0102] As an example of the present invention, refer to Figure 2 As shown, Figure 1 Detailed implementation steps of step S2 in the embodiment are shown in the flowchart. In this embodiment, step S2 includes:

[0103] Step S21: designing an underwater simulation topographic map framework based on the underwater GPS surveying and mapping data;

[0104] In an embodiment of the present invention, an underwater simulation topographic map architecture is designed based on underwater GPS surveying data. For example, these data are used to determine the coverage, resolution, and key topographic features of the simulation topographic map, and a topographic map covering an area of ​​1,000 square meters with a resolution of 1 meter is created, focusing on displaying information such as the slope of the terrain, the seabed structure, and the depth.

[0105] Step S22: collecting underwater obstacle data of the underwater area corresponding to the underwater GPS mapping data based on the sonar equipment to generate underwater obstacle data;

[0106] In an embodiment of the present invention, sonar equipment is used to collect underwater obstacle data for the area corresponding to the underwater GPS mapping data, including using a side-scan sonar or a multi-beam sonar system to carefully scan all potential obstacles in the area, such as shipwrecks, rocks or coral reefs. These data are used to generate underwater obstacle data and mark the location, size and shape of all obstacles.

[0107] Step S23: collecting hydrological information data for the underwater area corresponding to the underwater GPS surveying and mapping data to generate hydrological data;

[0108] In an embodiment of the present invention, hydrological information data is collected for the underwater area corresponding to the underwater GPS mapping data to supplement the terrain and obstacle information, which involves measuring information such as water flow speed and direction, using equipment such as CTD (Conductivity, Temperature, Depth) probes, and recording these water flow-related information to generate hydrological data.

[0109] Step S24: performing three-dimensional modeling of an initial underwater simulation topographic map based on the underwater simulation topographic map framework, underwater obstacle data, and hydrological data to establish an initial underwater simulation topographic map;

[0110] In an embodiment of the present invention, a three-dimensional modeling of an initial underwater simulation topographic map is performed based on the underwater simulation topographic map framework, underwater obstacle data, and hydrological data that have been collected. Using three-dimensional modeling software, such as AutoCAD Civil 3D or Rhino 3D, the underwater GPS mapping data is converted into a three-dimensional terrain model, assuming that these data show the topographic changes in a specific sea area, such as a slope with a depth gradually increasing from 5 meters to 30 meters, and some irregular seabed bumps. The underwater obstacle data obtained by the sonar device is integrated into the model. For example, if large rocks or shipwrecks are found in a certain area, the location, size, and shape of these obstacles will be accurately reflected in the three-dimensional model. For example, rocks may be marked as circular protrusions with a diameter of 3 meters, and shipwrecks may be modeled as 20-meter-long linear structures. The hydrological data is integrated into the model, including information such as water flow speed and direction, which can be used to evaluate the potential impact of the environment on the riprap operation. For example, if the water flow speed is 1 meter per second and the direction points to the northeast, this information will be used to simulate the possible movement and deposition path of stones during the riprap process. This creates a detailed and accurate initial underwater simulation terrain map.

[0111] Step S25: transmitting the deposition coordinate data to the initial underwater simulation topographic map for coordinate mapping to generate a simulated underwater topographic map.

[0112] In the embodiment of the present invention, after completing the three-dimensional modeling of the initial underwater simulation topographic map, the deposition coordinate data is integrated into the model. It is assumed that the deposition coordinate data is obtained through the previous steps, and the specific location of the expected riprap deposition is specified, such as 35.12345 degrees north latitude and 120.56789 degrees east longitude. These coordinate data reflect the target area of ​​the riprap operation. Use three-dimensional modeling software, such as QGIS or AutoCAD Civil 3D, to import these deposition coordinate data into the initial underwater simulation topographic map. The specific operation is to create a new layer in the software, and then mark the deposition coordinate data on this layer in the form of points. Each point represents a predetermined deposition location, and these points will be accurately placed at the corresponding position of the three-dimensional terrain model according to the GPS coordinates. For example, the deposition coordinate points to a position on a slope, and the point will be placed at the corresponding position of the slope in the three-dimensional model, which can not only visualize the location of each predetermined deposition point, but also see their relative relationship with the surrounding terrain, such as the nearest obstacle or depth change. Through this coordinate mapping, the final simulated underwater terrain map is generated, which integrates the terrain, obstacles and the predetermined deposition point locations. It will be used for subsequent riprap path planning and simulation analysis, helping us to evaluate and optimize riprap strategies and ensure the accuracy and effectiveness of riprap operations.

[0113] Preferably, step S3 comprises the following steps:

[0114] Step S31: performing data analysis of sedimentation deviation impact according to the simulated underwater topographic map to generate sedimentation deviation impact data;

[0115] Step S32: performing a deposition reverse path analysis according to the deposition coordinate data and the deposition deviation impact data to generate reverse deposition path data;

[0116] Step S33: performing reverse deposition path abnormality division processing on the reverse deposition path data according to the underwater obstacle data to obtain normal deposition path data and abnormal deposition path data;

[0117] Step S34: performing correction and adjustment processing on the abnormal deposition path data to generate corrected deposition path data;

[0118] Step S35: integrating the conventional deposition path data and the modified deposition path data to generate adjusted deposition path data;

[0119] Step S36: performing deposition coordinate adjustment processing on the deposition coordinate data according to the adjusted deposition path data to generate adjusted deposition coordinate data;

[0120] Step S37: performing water surface impact coordinate analysis of the riprap according to the adjusted deposition coordinate data and the adjusted deposition path data to generate water surface impact coordinate data.

[0121] The present invention performs data analysis based on a simulated underwater topographic map to identify factors that may affect the deposition position and generate deposition deviation influence data. This analysis helps to predict and identify factors that may cause sediments to deviate from the predetermined position, such as water flow, topography, etc., so as to make adjustments and plans in advance to reduce deviations. Reverse path analysis is performed using deposition coordinate data and deposition deviation influence data to generate reverse deposition path data. By analyzing the expected deposition path, the movement trajectory of sediments underwater is more accurately predicted, the stone throwing position and method are optimized, and the deposition effect is ensured to be consistent with expectations. Underwater obstacle data is used to analyze the reverse deposition path, and conventional and abnormal paths are distinguished. By identifying and processing abnormal paths, potential risks and obstacles can be prevented in advance, the deposition path can be optimized, and the safety and effectiveness of the operation can be ensured. The deposition path identified as abnormal is corrected and adjusted to generate corrected deposition path data. The corrected path data helps to reduce the potential risks and uncertainties caused by the abnormal path, ensure that the sediment is deposited according to the optimal path, and improve the reliability and efficiency of the operation. Conventional deposition path data and corrected deposition path data are comprehensively integrated to generate adjusted deposition path data, which ensures the integrity and consistency of the deposition path data and provides an accurate and comprehensive reference for the stone throwing operation. By integrating the data, the final position of the sediment can be better predicted and planned, ensuring the efficiency and accuracy of the riprap operation. Based on the adjusted sediment path data, the sediment coordinate data is precisely adjusted to generate the adjusted sediment coordinate data, further optimizing the accuracy of the sediment coordinates and ensuring that the sediment can reach the predetermined position more accurately. By adjusting the sediment coordinates, the repeated operations caused by deviation from the predetermined position can be reduced, and resource utilization and operation efficiency can be improved. The surface impact coordinates of riprap are analyzed using the adjusted sediment coordinate data and sediment path data to generate surface impact coordinate data, which can predict the impact position of the riprap on the water surface and provide key information for the actual riprap operation. Accurate surface impact coordinate data not only improves the accuracy of the riprap operation, but also helps to avoid potential risks and obstacles and ensure the safety of the operation.

[0122] As an example of the present invention, refer to Figure 3 As shown, Figure 1 Detailed implementation steps of step S3 in the flowchart, in this example, step S3 includes:

[0123] Step S31: performing data analysis of sedimentation deviation impact according to the simulated underwater topographic map to generate sedimentation deviation impact data;

[0124] In an embodiment of the present invention, a simulated underwater topographic map is used to perform data analysis on the effect of sedimentation deviation, assuming that the target area is a complex seabed topography, including seabed gullies of different depths and some rocky areas. First, a fluid dynamics simulation script such as Matlab or Python is used to analyze the water flow characteristics of this area in detail. For example, the speed and direction changes of the water flow at different depths may be concerned, especially around the predetermined riprap area. Based on the results of the water flow analysis, the possibility of the riprap moving underwater is evaluated. For example, in a specific area, the water flow speed is 1 meter per second and is in the north direction, and the deviation distance and direction that the riprap may produce during the deposition process can be calculated. This calculation takes into account factors such as the size, shape and weight of the riprap, as well as the force of the water flow on them. These calculation results are summarized into sedimentation deviation effect data. For example, these data may show that under the current water flow conditions, the riprap may deviate about 2 meters northward along the predetermined drop point.

[0125] Step S32: performing a deposition reverse path analysis according to the deposition coordinate data and the deposition deviation impact data to generate reverse deposition path data;

[0126] In an embodiment of the present invention, a deposition reverse path analysis is performed to generate reverse deposition path data. Deposition deviation influence data and specific deposition coordinate data are used. According to the deposition deviation influence data, it is predicted that under the current water flow conditions, the riprap may deviate about 2 meters to the north. Using this information, a computer simulation software such as HydroCAD or Matlab is used to perform a reverse path analysis, in which the deposition point is set as the end point and the deposition deviation influence data is considered to calculate the initial position from which the riprap should start to fall so as to eventually reach the predetermined deposition point accurately. For example, if the expected deviation is 2 meters to the north, the reverse path analysis may indicate that the initial drop point should be set at 35.12343 degrees north latitude and 120.56789 degrees east longitude. Reverse deposition path data are thus generated, which indicate the specific position from which the riprap should start to fall under specific environmental conditions in order for the riprap to accurately reach the predetermined deposition point.

[0127] Step S33: performing reverse deposition path abnormality division processing on the reverse deposition path data according to the underwater obstacle data to obtain normal deposition path data and abnormal deposition path data;

[0128] In an embodiment of the present invention, the deposition path data obtained by reverse path analysis is processed by abnormal division to distinguish between conventional and abnormal deposition paths. It is necessary to refer to the underwater obstacle data collected in the previous step, which may include the location and size information of rocks, shipwrecks or other natural and man-made obstacles. For example, it is assumed that the underwater obstacle data shows that there is a large rock with a diameter of about 5 meters at 35.12340 degrees north latitude and 120.56785 degrees east longitude. These obstacle data are compared and analyzed with the reverse deposition path data, and GIS software or a customized analysis script is used to check whether each reverse deposition path intersects or is too close to any obstacle. For example, if a reverse path passes through the position of the above-mentioned rock, this path is marked as an abnormal deposition path, and such analysis results will be used to divide conventional deposition path data and abnormal deposition path data. Conventional paths are those paths that are not affected by obstacles, while abnormal paths are those paths that may cause the riprap to fail to reach the predetermined deposition point correctly due to obstacles. For example, paths that are not affected by rocks are regarded as conventional paths, while paths that pass through or are too close to rocks are regarded as abnormal paths.

[0129] Step S34: performing correction and adjustment processing on the abnormal deposition path data to generate corrected deposition path data;

[0130] In the embodiment of the present invention, the abnormal deposition path is corrected and adjusted. For example, if it is found that the deposition path intersects with a large rock, the path will be adjusted to avoid this obstacle, and the corrected deposition path data will be generated.

[0131] Step S35: integrating the conventional deposition path data and the modified deposition path data to generate adjusted deposition path data;

[0132] In the embodiment of the present invention, conventional deposition path data and modified deposition path data are integrated to generate adjusted deposition path data, and this data set becomes the final reference for the implementation of underwater riprap operation.

[0133] Step S36: performing deposition coordinate adjustment processing on the deposition coordinate data according to the adjusted deposition path data to generate adjusted deposition coordinate data;

[0134] In the embodiment of the present invention, the original deposition coordinate data is adjusted according to the adjusted deposition path data to generate the adjusted deposition coordinate data, so as to ensure that the riprap can accurately reach the predetermined deposition position, taking into account the influence of factors such as water flow and obstacles on the deposition path. Assuming that the original deposition coordinates are 35.12345 degrees north latitude and 120.56789 degrees east longitude, according to the analysis of the previous steps, it is known that due to the influence of water flow, the riprap will actually be deposited at 35.12350 degrees north latitude and 120.56785 degrees east longitude, so the original deposition coordinates need to be adjusted. Using computer-aided design software (such as AutoCAD or QGIS), input the adjusted deposition path data, and compare these data with the original deposition coordinates to calculate how much adjustment needs to be made to the original coordinates to ensure that the riprap can reach the target position along the adjusted path. For example, it is calculated that in order to compensate for the offset caused by water flow, the original deposition coordinates need to be offset 5 meters to the south and 3 meters to the west. Therefore, the adjusted deposition coordinates will be 35.12340 degrees north latitude and 120.56782 degrees east longitude, thus generating adjusted deposition coordinate data.

[0135] Step S37: performing water surface impact coordinate analysis of the riprap according to the adjusted deposition coordinate data and the adjusted deposition path data to generate water surface impact coordinate data.

[0136] In the embodiment of the present invention, the water surface impact coordinate analysis of the riprap is performed based on the adjusted deposition coordinate data and deposition path data to determine the optimal position where the riprap contacts the water surface, thereby ensuring that it is accurately deposited to the adjusted coordinate position along the predetermined path. Assuming that the adjusted deposition coordinates are 35.12340 degrees north latitude and 120.56782 degrees east longitude, and based on the deposition path data, it is known that the riprap needs to fall from a certain point on the water surface to reach this position, special physical simulation software, such as ANSYS Fluent or OpenFOAM, is used to perform this analysis, which can simulate the entire process of the riprap falling from the water surface to the deposition point, taking into account water flow, water depth and other relevant physical factors. For example, through simulation analysis, in order to ensure that the riprap can accurately reach the deposition position at 35.12340 degrees north latitude and 120.56782 degrees east longitude, the riprap should start to fall from the position of 35.12345 degrees north latitude and 120.56785 degrees east longitude on the water surface. This calculation takes into account factors such as the speed and direction of the water flow, the weight and shape of the riprap. This water surface impact coordinate point is marked on the underwater simulation topographic map, and the water surface impact coordinate data is generated, which provides key information for the actual riprap operation, ensuring that the riprap can fall and deposit according to the predetermined trajectory, thereby determining the optimal water surface impact coordinate.

[0137] Preferably, step S31 includes the following steps:

[0138] Collecting sedimentation depth data according to the simulated underwater topographic map and the sedimentation coordinate data to obtain sedimentation depth data;

[0139] Data analysis of sedimentation deviation impact is performed based on the sedimentation depth data and the hydrological data to generate sedimentation deviation impact data.

[0140] The present invention collects data on sediment depth based on simulated underwater topographic maps and sediment coordinate data to obtain information on the depth to which sediments may settle, and provides specific depth information that sediments may reach underwater, which is crucial for accurately predicting the final position of sediments. Accurate sediment depth data helps optimize the stone throwing strategy to ensure that sediments can effectively reach the predetermined position. Sediment depth data and hydrological data can be analyzed by fluid dynamics technology and other technologies to evaluate factors that may affect sediment deviation, such as water flow, hydrodynamic characteristics, etc. This analysis helps to understand and predict the behavior of sediments in underwater environments, especially in areas where fluid dynamics have a significant impact, to predict possible deviations of sediments, so as to make necessary adjustments and optimizations before actual stone throwing, reduce deviations, and ensure that sediments reach the predetermined position more accurately.

[0141] In the embodiment of the present invention, the sedimentation depth data is collected according to the simulated underwater topographic map and the sedimentation coordinate data. Assuming that our sedimentation coordinate is 35.12345 degrees north latitude and 120.56789 degrees east longitude, the specific water depth of this coordinate point can be determined by using the simulated underwater topographic map. For example, the topographic map may show that the water depth here is 25 meters. Next, the data analysis of the sedimentation deviation effect will be performed based on this sedimentation depth data and the collected hydrological data. The hydrological data may include the water flow velocity, direction and water quality characteristics of the area. For example, the hydrological data may show that the water flow velocity at this sedimentation point is 0.5 meters per second and the direction is east. We use this information to evaluate and calculate the possible deviation of the riprap during the underwater sedimentation process. This may involve using a fluid dynamics model or computing software, such as ANSYS Fluent, to simulate the sinking process of the riprap and predict its final sedimentation position. For example, based on the fluid dynamics analysis, it may be concluded that due to the influence of the water flow, the riprap may deviate to the east by about 2 meters during the sinking process. In this way, the sedimentation deviation effect data, that is, the expected offset distance and direction, is obtained. Combined with these analysis results, the sediment deviation impact data provides us with important information to help adjust the rock dumping strategy in the subsequent steps to ensure that the rocks can accurately reach the intended deposition point. By considering the impact of sedimentation depth and hydrological conditions, we can plan and execute underwater rock dumping operations more effectively.

[0142] Preferably, step S34 includes the following steps:

[0143] Extracting abnormal riprap deposition nodes from the abnormal deposition path data to obtain abnormal deposition nodes;

[0144] Performing analysis and processing on traversable riprap deposition nodes according to the abnormal deposition nodes to generate traversable deposition nodes;

[0145] Performing a preferred feature node extraction process on the traversable deposition node to generate a traversable deposition feature node;

[0146] The number of abnormal deposition paths is corrected and adjusted according to the passable deposition feature nodes to generate corrected deposition path data.

[0147] The present invention extracts abnormal deposition nodes from abnormal deposition path data. These nodes are key points that cause the deposition path to deviate. Identifying these abnormal nodes helps to accurately locate the specific location that causes the deposition path to deviate, so that the correction process is more targeted, which is the premise for correcting the abnormal path and provides a basis for subsequent optimization. Analysis is performed based on abnormal deposition nodes to determine passable deposition nodes, thereby generating passable deposition nodes, which helps to distinguish those nodes that may become passable through adjustment, thereby optimizing the entire deposition path, reducing obstacles and risks in the deposition process, and ensuring the smooth deposition of sediments. Nodes with key or advantageous features are further extracted from the passable deposition nodes, which are called passable deposition feature nodes, such as the passable deposition nodes closest to the original nodes. By identifying these feature nodes, the deposition path is more effectively optimized, ensuring the efficiency and safety of the riprap deposition process. The extraction of feature nodes is a key step in achieving path optimization. Based on the passable deposition feature nodes, the abnormal deposition path data is corrected and adjusted to generate the corrected deposition path data, which can effectively correct the original abnormal path, reduce errors and risks in the deposition process, and ensure that the sediments arrive at the predetermined position smoothly according to the optimal path.

[0148] In an embodiment of the present invention, the identified abnormal deposition path data is analyzed to extract abnormal riprap deposition nodes. Assuming that the abnormal path is marked as abnormal because it encounters a large shipwreck obstacle, the coordinates of the shipwreck are 35.12360 degrees north latitude and 120.56795 degrees east longitude, and the depth is 5 meters, GIS software or a custom analysis script is used to identify the riprap path points that collide with the shipwreck, mark them as abnormal deposition nodes, and extract the corresponding nodes of the abnormal deposition nodes that can bypass the shipwreck part to obtain passable deposition nodes. The node with the shortest distance from the passable nodes corresponding to the abnormal deposition nodes is selected and marked as a feature node. The feature node ensures that when the abnormal riprap deposition path is passable, the minimum impact on the target position during the riprap process is generated, and a passable deposition feature node is generated. The original abnormal deposition path is corrected and adjusted according to the passable deposition feature node. Using path planning software, such as HydroCAD, the original path that directly passed through the shipwreck obstacle was adjusted to bypass the obstacle to ensure that the riprap could safely reach the characteristic node. The modified deposition path data generated in this way took into account safety and feasibility, ensuring the successful execution of the riprap operation.

[0149] Preferably, step S4 comprises the following steps:

[0150] Step S41: designing a water surface riprap delivery strategy according to the water surface impact coordinate data;

[0151] Step S42: performing underwater riprap operation according to the surface riprap delivery strategy, and collecting actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data;

[0152] Step S43: performing deposition deviation distance calculation on the actual deposition coordinate data according to the adjusted deposition coordinate data to generate deposition deviation distance data of the actual deposition coordinate data;

[0153] Step S44: when the deposition deviation distance data is greater than a preset deposition deviation threshold, the surface riprap delivery strategy is iteratively updated and optimized.

[0154] The present invention designs a specific delivery strategy for surface riprap based on the surface impact coordinate data, ensuring that the initial strategy of the riprap operation can minimize the deposition deviation and improve the accuracy of the deposition. A reasonable delivery strategy is the basis for achieving efficient deposition, and significantly improves the efficiency and accuracy of underwater riprap operations. According to the designed delivery strategy, the actual underwater riprap operation is performed, and the actual coordinate data after deposition is collected. The collection of the actual deposition coordinate data is crucial for evaluating the effectiveness of the delivery strategy, ensuring that there is sufficient data support to analyze and optimize the delivery strategy. Based on the adjusted deposition coordinate data and the actual deposition coordinate data, the deposition deviation distance is calculated. The calculated deviation distance data provides direct feedback on the accuracy of the current delivery strategy, and is a key data indicator for evaluating and optimizing the strategy. When the deposition deviation distance exceeds the preset threshold, the delivery strategy is iteratively updated and optimized. This dynamic adjustment mechanism allows the delivery strategy to be continuously optimized according to the actual operation situation, ensuring the continuous improvement of the accuracy and efficiency of the deposition operation. This iterative update is the key to continuous improvement and adaptation to the ever-changing environment.

[0155] As an example of the present invention, refer to Figure 4 As shown, Figure 1 Detailed implementation steps of step S4 in the embodiment are shown in the flowchart. In this embodiment, step S4 includes:

[0156] Step S41: designing a water surface riprap delivery strategy according to the water surface impact coordinate data;

[0157] In the embodiment of the present invention, a surface riprap strategy is designed based on the surface impact coordinate data. Assume that the surface impact coordinate data shows that the best riprap point is located at 35.12345 degrees north latitude and 120.56789 degrees east longitude. According to this coordinate, it is planned to use specific riprap equipment, such as a riprap boat with high positioning accuracy, to riprap at a predetermined speed and angle to ensure that the riprap can accurately land on the target point on the water surface.

[0158] Step S42: performing underwater riprap operation according to the surface riprap delivery strategy, and collecting actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data;

[0159] In the embodiment of the present invention, the underwater riprap operation is performed according to the designed strategy, and the actual deposition coordinates are collected using a high-precision GPS device carried on the riprap ship. For example, after the riprap operation is performed, the GPS data shows that the actual deposition coordinates are 35.12347 degrees north latitude and 120.56791 degrees east longitude.

[0160] Step S43: performing deposition deviation distance calculation on the actual deposition coordinate data according to the adjusted deposition coordinate data to generate deposition deviation distance data of the actual deposition coordinate data;

[0161] In the embodiment of the present invention, the actual deposition coordinate data and the adjusted deposition coordinate data are compared and analyzed to calculate the deposition deviation distance. For example, if the adjusted coordinates are 35.12345 degrees north latitude and 120.56789 degrees east longitude, then the actual deposition coordinates are compared with the deviation distance, which can be obtained by calculating the straight-line distance between the two points to generate the deposition deviation distance data of the actual deposition coordinate data.

[0162] Step S44: when the deposition deviation distance data is greater than a preset deposition deviation threshold, the surface riprap delivery strategy is iteratively updated and optimized.

[0163] In an embodiment of the present invention, if the deposition deviation distance exceeds a preset deposition deviation threshold, for example, the set threshold is 1 meter, and the actual deviation is 2 meters, we need to iteratively update and optimize the surface stone throwing strategy, including adjusting the stone throwing angle, speed or positioning accuracy of the stone throwing equipment.

[0164] Preferably, step S44 includes the following steps:

[0165] When the deposition deviation distance data is greater than a preset deposition deviation threshold, the surface riprap delivery strategy corresponding to the deposition deviation distance data is marked as an abnormal riprap delivery strategy;

[0166] According to the preset intelligent tuning model, the abnormal riprap delivery strategy is optimized and adjusted to generate an optimized surface riprap delivery strategy;

[0167] The optimized surface riprap delivery strategy is fed back to the surface riprap delivery strategy of step S41 for iterative update and optimization.

[0168] In the present invention, when the sediment deviation distance data exceeds a preset threshold, the corresponding surface riprap delivery strategy is marked as abnormal, so that the delivery strategy that needs to be improved can be quickly identified, providing a clear goal for subsequent optimization. This is an important data self-assessment mechanism to ensure continuous monitoring and improvement of the accuracy of the delivery strategy. The delivery strategy marked as abnormal is optimized and adjusted using a preset intelligent tuning model to generate an optimized delivery strategy. The application of the intelligent tuning model makes the strategy optimization process more efficient and accurate. This data-driven optimization method can quickly respond to challenges in actual operations and improve the deposition accuracy of underwater riprap operations. The optimized delivery strategy is fed back to step S41 for iterative update and optimization. The iterative update mechanism ensures that the delivery strategy can continuously adapt to changes in actual operating conditions, thereby continuously improving the efficiency and accuracy of riprap operations, strengthening the learning and adaptability of the entire system, and providing motivation for continuous improvement and optimization of operating methods.

[0169] In an embodiment of the present invention, a preset sedimentation deviation threshold is set, such as 1 meter. When the sedimentation deviation distance data exceeds this threshold through the analysis of step S43, for example, the actual sedimentation deviation distance is 1.5 meters, we mark the surface riprap delivery strategy corresponding to the riprap operation as abnormal. After determining that the abnormal riprap delivery strategy needs to be optimized and adjusted, we first set a preset intelligent tuning model, which may be a model based on machine learning, such as a deep neural network. This model has been trained with historical riprap data and can predict the optimal riprap parameters based on input sedimentation deviation distance data and hydrological data and other factors. For example, suppose that in a riprap operation, we observe that the sedimentation deviation distance is 1.5 meters, and the hydrological data shows that the water flow velocity is 0.5 meters per second, and the direction is east. These data are input into the intelligent tuning model, and the model analyzes this information and predicts the riprap parameters that need to be adjusted in order to reduce the sedimentation deviation. For example, the model may suggest adjusting the angle of the riprap point from 45 degrees to 50 degrees and reducing the riprap speed from 2 meters / second to 1.8 meters / second. According to these predictions of the model, we adjust the strategy influencing parameters of the surface riprap strategy, including the influence of hydrological data on the surface riprap, and adopt new riprap angles and speeds. Through this optimization adjustment, the accuracy of riprap is improved. This optimized strategy is fed back to the surface riprap strategy of step S41 for iterative update optimization. In the next riprap operation, we will apply this new optimization strategy in the hope of reducing deposition deviation and improving accuracy.

[0170] Preferably, the optimization and adjustment of the abnormal riprap strategy according to the preset intelligent tuning model includes the following steps:

[0171] Integrate the feedback data of abnormal riprap placement according to the abnormal riprap placement strategy to obtain abnormal riprap feedback data, wherein the abnormal riprap feedback data includes sedimentation deviation distance data and hydrological data corresponding to the abnormal riprap placement strategy;

[0172] Transmitting the abnormal riprap feedback data to a preset intelligent tuning model to perform optimization parameter prediction processing of the abnormal riprap delivery strategy to generate optimization parameters;

[0173] The abnormal riprap delivery strategy is optimized and adjusted according to the optimization parameters to generate an optimized surface riprap delivery strategy.

[0174] The present invention collects and integrates feedback data of abnormal rock dumping strategies, including sediment deviation distance data and hydrological data related to the strategy, and provides a comprehensive data view, which helps to deeply understand the specific factors that cause the strategy abnormality. The integrated data provides necessary input for the intelligent model, increasing the accuracy and effectiveness of optimization. The abnormal rock dumping feedback data is input into the preset intelligent tuning model to predict the optimization parameters of the strategy. The intelligent model can predict the optimal adjustment parameters based on actual data. This data-driven prediction improves the accuracy and efficiency of optimization. The application of the model can quickly identify the most effective adjustment strategy and reduce trial and error time. According to the optimization parameters predicted by the intelligent model, the abnormal rock dumping strategy is adjusted to generate an optimized strategy, so that the delivery strategy can be accurately adjusted according to the actual operation feedback, improving the accuracy and adaptability of the operation. Through optimization and adjustment, the strategy becomes more flexible and effective to cope with complex and changeable underwater environments.

[0175] In an embodiment of the present invention, after the abnormal riprap delivery strategy is identified, feedback data is integrated. This includes collecting data directly related to the abnormal riprap delivery strategy, such as deposition deviation distance data and hydrological data. For example, assuming that in a specific riprap operation, the deposition deviation distance is 1.5 meters, and the hydrological data shows that the water flow velocity in the riprap area is 0.5 meters per second, and the direction is east. Then, these abnormal riprap feedback data are input into a preset intelligent tuning model. This model may be a neural network based on deep learning, which has been trained with historical data and can identify the influence of different parameters, such as hydrological data, on the deposition deviation. The model analyzes the feedback data and predicts which optimization parameters can reduce the deposition deviation in future operations, and continuously trains the intelligent tuning model in this way. For example, the intelligent tuning model once again analyzes the feedback data to update the specific influence of the hydrological data on the riprap deposition process, so that the tuning model continuously optimizes the underwater riprap delivery strategy, and then obtains the optimization parameters of the abnormal riprap delivery strategy. According to the optimization parameters provided by the intelligent tuning model, the abnormal riprap delivery strategy is adjusted. This means that in the next operation, these new parameters will be adopted in the hope of obtaining more accurate deposition results, thereby generating an optimized surface riprap placement strategy.

[0176] This specification provides a high-precision underwater riprap system based on GPS positioning, which is used to execute the high-precision underwater riprap method based on GPS positioning as described above. The high-precision underwater riprap system based on GPS positioning includes:

[0177] A deposition coordinate data acquisition module is used to obtain riprap deposition coordinate instructions; based on GPS technology and the riprap deposition coordinate instructions, riprap coordinates are collected to obtain deposition coordinate data;

[0178] A simulated underwater topographic map establishment module is used to establish an initial underwater simulated topographic map; the deposition coordinate data is transmitted to the initial underwater simulated topographic map for coordinate mapping to generate a simulated underwater topographic map;

[0179] A water surface impact coordinate data analysis module, used for performing water surface impact coordinate analysis of riprap according to the simulated underwater topographic map and the deposition coordinate data to generate water surface impact coordinate data;

[0180] The underwater riprap operation module is used to design a surface riprap delivery strategy according to the surface impact coordinate data; perform underwater riprap operation according to the surface riprap delivery strategy, and collect actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data; and iteratively update and optimize the surface riprap delivery strategy according to the actual deposition coordinate data.

[0181] The beneficial effect of the present application is that the high-precision underwater riprap method based on GPS positioning of the present invention relies on accurate GPS positioning technology and simulated riprap simulation technology, and can more accurately find the target deposition position of underwater riprap and the simulated deposition path existing in underwater riprap, so that the accuracy and efficiency of underwater riprap are higher, and the influence of hydrological data on riprap during underwater riprap can be considered, and then the data parameters in the underwater riprap process can be continuously iterated and optimized, so that the accuracy of underwater riprap is higher.

[0182] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0183] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A high-precision underwater riprap method based on GPS positioning, characterized in that: The following steps are involved: Step S1: obtaining a riprap deposition coordinate instruction; collecting riprap coordinates based on GPS technology and the riprap deposition coordinate instruction to obtain deposition coordinate data; Wherein, step S1 includes the following steps: obtaining a riprap deposition coordinate instruction; performing data analysis on the riprap deposition coordinate instruction to generate instruction analysis data, wherein the instruction analysis data includes riprap deposition area data and riprap deposition positioning data; collecting underwater GPS mapping data of the riprap deposition area data through GPS technology; collecting riprap coordinates according to the riprap deposition positioning data and the underwater GPS mapping data to obtain deposition coordinate data; Step S2: establishing an initial underwater simulated topographic map; transmitting the deposition coordinate data to the initial underwater simulated topographic map for coordinate mapping to generate a simulated underwater topographic map; Wherein, step S2 comprises the following steps: Step S21: designing an underwater simulation topographic map framework based on the underwater GPS surveying and mapping data; Step S22: collecting underwater obstacle data of the underwater area corresponding to the underwater GPS mapping data based on the sonar equipment to generate underwater obstacle data; Step S23: collecting hydrological information data for the underwater area corresponding to the underwater GPS surveying and mapping data to generate hydrological data; Step S24: performing three-dimensional modeling of an initial underwater simulation topographic map based on the underwater simulation topographic map framework, underwater obstacle data, and hydrological data to establish an initial underwater simulation topographic map; Step S25: transmitting the deposition coordinate data to the initial underwater simulation topographic map for coordinate mapping to generate a simulated underwater topographic map; Step S3: performing a water surface impact coordinate analysis of the riprap according to the simulated underwater topographic map and the deposition coordinate data to generate water surface impact coordinate data; Wherein, step S3 comprises the following steps: Step S31: performing data analysis of sedimentation deviation impact according to the simulated underwater topographic map to generate sedimentation deviation impact data; Wherein, step S31 includes the following steps: Collecting sedimentation depth data according to the simulated underwater topographic map and the sedimentation coordinate data to obtain sedimentation depth data; Performing data analysis on the impact of sedimentation deviation based on the sedimentation depth data and the hydrological data to generate sedimentation deviation impact data; Step S32: performing a deposition reverse path analysis according to the deposition coordinate data and the deposition deviation impact data to generate reverse deposition path data; Step S33: performing reverse deposition path abnormality division processing on the reverse deposition path data according to the underwater obstacle data to obtain normal deposition path data and abnormal deposition path data; Step S34: performing correction and adjustment processing on the abnormal deposition path data to generate corrected deposition path data; Wherein, step S34 comprises the following steps: Extracting abnormal riprap deposition nodes from the abnormal deposition path data to obtain abnormal deposition nodes; Performing analysis and processing on traversable riprap deposition nodes according to the abnormal deposition nodes to generate traversable deposition nodes; Performing a preferred feature node extraction process on the traversable deposition node to generate a traversable deposition feature node; Correcting and adjusting the number of abnormal deposition paths according to the passable deposition feature nodes to generate corrected deposition path data; Step S35: integrating the conventional deposition path data and the modified deposition path data to generate adjusted deposition path data; Step S36: performing deposition coordinate adjustment processing on the deposition coordinate data according to the adjusted deposition path data to generate adjusted deposition coordinate data; Step S37: performing water surface impact coordinate analysis of the riprap according to the adjusted deposition coordinate data and the adjusted deposition path data to generate water surface impact coordinate data; Step S4: designing a surface riprap delivery strategy according to the surface impact coordinate data; performing underwater riprap operation according to the surface riprap delivery strategy, and collecting actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data; and iteratively updating and optimizing the surface riprap delivery strategy according to the actual deposition coordinate data.

2. The high-precision underwater riprap method based on GPS positioning according to claim 1 is characterized in that: Step S4 includes the following steps: Step S41: designing a water surface riprap delivery strategy according to the water surface impact coordinate data; Step S42: performing underwater riprap operation according to the surface riprap delivery strategy, and collecting actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data; Step S43: performing deposition deviation distance calculation on the actual deposition coordinate data according to the adjusted deposition coordinate data to generate deposition deviation distance data of the actual deposition coordinate data; Step S44: when the deposition deviation distance data is greater than a preset deposition deviation threshold, the surface riprap delivery strategy is iteratively updated and optimized.

3. The high-precision underwater riprap method based on GPS positioning according to claim 2 is characterized in that: Step S44 includes the following steps: When the deposition deviation distance data is greater than a preset deposition deviation threshold, the surface riprap delivery strategy corresponding to the deposition deviation distance data is marked as an abnormal riprap delivery strategy; According to the preset intelligent tuning model, the abnormal riprap delivery strategy is optimized and adjusted to generate an optimized surface riprap delivery strategy; The optimized surface riprap delivery strategy is fed back to the surface riprap delivery strategy of step S41 for iterative update and optimization.

4. The high-precision underwater riprap method based on GPS positioning according to claim 3 is characterized in that: The optimization and adjustment of the abnormal riprap strategy according to the preset intelligent tuning model includes the following steps: Integrate the feedback data of abnormal riprap placement according to the abnormal riprap placement strategy to obtain abnormal riprap feedback data, wherein the abnormal riprap feedback data includes sedimentation deviation distance data and hydrological data corresponding to the abnormal riprap placement strategy; Transmitting the abnormal riprap feedback data to a preset intelligent tuning model to perform optimization parameter prediction processing of the abnormal riprap delivery strategy to generate optimization parameters; The abnormal riprap delivery strategy is optimized and adjusted according to the optimization parameters to generate an optimized surface riprap delivery strategy.

5. A high-precision underwater riprap system based on GPS positioning, characterized in that: Used to execute the high-precision underwater riprap method based on GPS positioning as claimed in claim 1, the high-precision underwater riprap system based on GPS positioning comprises: A deposition coordinate data acquisition module is used to obtain riprap deposition coordinate instructions; based on GPS technology and the riprap deposition coordinate instructions, riprap coordinates are collected to obtain deposition coordinate data; A simulated underwater topographic map establishment module is used to establish an initial underwater simulated topographic map; the deposition coordinate data is transmitted to the initial underwater simulated topographic map for coordinate mapping to generate a simulated underwater topographic map; A water surface impact coordinate data analysis module, used for performing water surface impact coordinate analysis of riprap according to the simulated underwater topographic map and the deposition coordinate data to generate water surface impact coordinate data; The underwater riprap operation module is used to design a surface riprap delivery strategy according to the surface impact coordinate data; perform underwater riprap operation according to the surface riprap delivery strategy, and collect actual deposition coordinates of the underwater riprap operation to obtain actual deposition coordinate data; and iteratively update and optimize the surface riprap delivery strategy according to the actual deposition coordinate data.

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