Ship interaction effect analysis and coping method based on digital twin technology

Abstract

The application discloses a ship interaction effect analysis and response method based on a digital twinborn technology, relates to the technical field of ship interaction control, and comprises the following steps: installing corresponding Internet of Things equipment around a ship body, collecting ship body surrounding environment data and ship body data in real time based on the installed Internet of Things equipment, processing the ship body surrounding environment data and the ship body data collected by the Internet of Things equipment after the collection is completed, obtaining a three-dimensional geometric model of the ship body and processed ship body surrounding environment data, constructing a ship body motion mathematical model through a data simulation mode based on the three-dimensional geometric model of the ship body and the processed ship body surrounding environment data after the processing is completed, and finally planning two-ship encounter and overtaking problems based on the ship body motion mathematical model and performing real-time auxiliary control adjustment on the ship body based on real-time sensing of the surrounding environment during the sailing process, so that the accuracy of the ship auxiliary control planning is improved.

Description

Technical Field

[0001] This invention relates to the field of ship-to-ship control technology, specifically to methods for analyzing and addressing ship-to-ship effects based on digital twin technology. Background Technology

[0002] As ships gradually become larger and more specialized, it is common for them to overtake or sail in opposite directions when entering or leaving ports. When ships sail in parallel, navigational interference caused by their interaction is inevitable. Ships may collide due to mutual attraction and changes in their heading. If repulsion and stern drift occur, ships severely affected by the interference are prone to losing control and colliding with other nearby vessels. For smaller ships, the effects of disturbances from larger ships are quite significant, making collisions more likely due to delayed rudder response or ineffective avoidance. Summary of the Invention

[0003] The purpose of this invention is to provide a method for analyzing and addressing ship-to-ship effects based on digital twin technology, thereby solving the problems existing in the background technology.

[0004] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The present invention provides a method for analyzing and responding to ship-to-ship effects based on digital twin technology, specifically including the following steps: S1. Install corresponding Internet of Things (IoT) devices around the hull, including: positioning sensors, cameras, and lidar; S2. Real-time collection of environmental data around the ship and ship data based on installed IoT devices; The data on the environment surrounding the hull includes: inter-ship force data and point cloud data of the environment surrounding the hull. S3. Process the environmental data around the ship and the ship data collected by the IoT device to obtain the three-dimensional geometric model of the ship and the processed environmental data around the ship. S4. Based on the three-dimensional geometric model of the hull and the processed environmental data around the hull, construct a mathematical model of hull motion through data simulation. S5. Based on the mathematical model of ship motion, plan the encounter and overtaking problems of two ships, and perform real-time auxiliary control and adjustment of the ship based on the real-time perception of the surrounding environment during the operation.

[0005] Preferably, the real-time collection of environmental data and hull data based on the installed IoT device includes the following steps: S21. Divide the surrounding environment of the ship into grids to obtain the divided surrounding environment of the ship. Set the center coordinates of the area surrounding the ship's hull, and construct a coordinate system based on the set center coordinates; Set the unit distance for constructing the coordinate system, and divide the surrounding environment area of ​​the ship based on the set unit distance to obtain the divided surrounding environment area of ​​the ship. S22. Set a data collection period based on the divided environmental area around the hull, and collect environmental data and hull data within the divided environmental area around the hull based on the set data collection period.

[0006] Preferably, the step of setting a data collection period based on the divided environmental area surrounding the hull, and collecting environmental data and hull data within the divided environmental area surrounding the hull based on the set data collection period, includes the following steps: Set data collection cycle set , Indicates the set number One collection cycle, Indicates the total number of set data collection cycles; Set up a primary acquisition device and a backup acquisition device; use the primary acquisition device and the backup acquisition device to collect data on the surrounding environment and the ship itself within the divided area of ​​the surrounding environment, and set up redundancy between the primary acquisition device and the backup acquisition device. When the main acquisition device is not malfunctioning, according to the data acquisition cycle set The data on the surrounding environment and the ship itself collected by the main acquisition device are used as the real-time data on the surrounding environment and the ship itself. When the main acquisition device malfunctions, the environmental data around the ship and the ship data collected by the main acquisition device will be used as the real-time environmental data around the ship and the ship data.

[0007] Preferably, the process of processing the environmental data around the hull and the hull data collected by the IoT device to obtain the three-dimensional geometric model of the hull and the processed environmental data around the hull includes the following steps: S31. The collected environmental data around the ship is processed using data processing methods to obtain processed environmental data around the ship. S32. The collected hull data is processed using 3D modeling methods to obtain a 3D geometric model of the hull.

[0008] Preferably, the process of processing the collected environmental data around the ship hull using a data processing method to obtain processed environmental data around the ship hull includes the following steps: S311. The collected data on the environment around the ship is standardized using a data standardization method to obtain standardized data on the environment around the ship. The standardization formula is as follows: ; in, This represents the minimum value of the environmental data surrounding the ship's hull. This represents the maximum value of the environmental data surrounding the ship's hull. This represents the collected data on the environment surrounding the ship's hull. This represents standardized data on the environment surrounding the ship's hull. S312. Based on the standardized environmental data surrounding the hull, perform positioning correction and target detection on the environmental data surrounding the hull.

[0009] Preferably, the positioning correction and target detection of the ship's surrounding environment data based on the standardized data includes the following steps: The standardized environmental data surrounding the ship's hull is defined as point cloud data. Using the lidar itself as the origin and the lidar's sensing range as the radius, the coordinate plane is divided into grids of fixed size. Point cloud pillars are constructed in conjunction with the Z-axis of the coordinate system. Each point cloud pillar contains several points. N is set as the number of points and D as the number of dimensions. The point cloud data acquired by the lidar is averaged by comparing multiple frames. The collected point cloud data is transmitted to a trained neural network for feature extraction. Based on the feature extraction, objects are identified and the feature points of the corresponding objects are saved. The coordinate position of the target object is determined based on the saved feature points and the constructed coordinate system. After the coordinate position is determined, feature extraction is performed on another frame of point cloud data to obtain the new coordinate position, and it is compared with the feature points of the previous frame. If the overlap is higher than 80%, the target detection is performed based on this. The point cloud data of adjacent frames are calculated using the mean algorithm, and the location correction of the surrounding environment data of the ship is performed based on the mean calculation results.

[0010] Preferably, the process of processing the collected hull data using a 3D modeling method to obtain a 3D geometric model of the hull includes the following steps: The collected ship hull data is stitched together using a target stitching method; Each area of ​​the ship's hull is numbered, and multiple monitoring points are set up in each area of ​​the ship's hull; Place three or more targets in the common area between two adjacent monitoring points; The data and targets at each monitoring point are scanned sequentially using lidar and cameras; After the scan is completed, the data and targets from the non-monitoring points are stitched together to obtain a three-dimensional geometric model of the ship's hull.

[0011] Preferably, the process of constructing a mathematical model of hull motion based on the three-dimensional geometric model of the hull and the processed environmental data surrounding the hull through data simulation includes the following steps: The three-dimensional geometric model of the hull and the processed data of the surrounding environment of the hull are rasterized to determine the coordinates of the hull and the surrounding environment data in the raster network. A mathematical model of hull motion is constructed based on the coordinates of the hull and the surrounding environment data in the grid network determined within adjacent acquisition cycles. The ship's motion model is shown below: ; in, This represents the position coordinates of the ship's hull in the established coordinate system at time t. This represents the position coordinates of the ship's hull in the established coordinate system at time t-1. This represents the measurement data from the ship's hull monitoring equipment at time t. This represents the data of inter-ship force detected by the ship monitoring equipment at time t during the measurement process. Represents the equations of motion for the ship's hull. Indicates about and The equations of motion for the ship's hull.

[0012] Preferably, the process of planning the encounter and overtaking problems between two ships based on the mathematical model of ship motion, and adjusting the ship's hull in real time based on real-time perception of the surrounding environment during navigation, includes the following steps: The initial stage of a confrontation is defined as the bows of the two ships meeting, ending when the sterns of the two ships separate from contact; the starting point of the overtaking phenomenon is the intersection of the bow of the overtaking ship and the stern of the overtaken ship, ending when the stern of the overtaking ship surpasses the bow of the overtaken ship. The planning of the two-ship encounter and overtaking problem based on the mathematical model of ship motion includes the following steps: First, a three-dimensional geometric model of the ship's hull is constructed. After the geometric modeling is completed, the mathematical model of the ship's motion is used to calculate the ship's position coordinates in real time, while defining the calculation area for when the two ships meet. After defining the calculation area for the encounter between the two ships, the environmental data around the ship's hull is discretized into a grid. Then, appropriate boundary constraints are configured, and a solver is used to perform numerical solutions to calculate the real-time auxiliary control parameters of the ship's hull.

[0013] The present invention also provides a method for analyzing and responding to ship-to-ship effects based on digital twin technology, which further includes: a data acquisition module, a data processing module, a ship motion analysis module, and an auxiliary control module; The data acquisition module is used to collect real-time data on the surrounding environment and hull data. The data processing module is used to process the real-time collected data on the surrounding environment and the ship data to obtain a three-dimensional geometric model of the ship and the processed data on the surrounding environment. The hull motion analysis module is used to construct a mathematical model of hull motion through data simulation based on the three-dimensional geometric model of the hull and the processed data of the surrounding environment of the hull. The auxiliary control module is used to plan the encounter and overtaking problems of two ships based on the mathematical model of ship motion, and to make real-time auxiliary control adjustments to the ship based on the real-time perception of the surrounding environment during the operation.

[0014] The beneficial effects of this invention are as follows: (1) This invention installs corresponding Internet of Things (IoT) devices around the hull and collects data on the surrounding environment and the hull in real time based on the installed IoT devices. After the data collection is completed, the data on the surrounding environment and the hull collected by the IoT devices are processed to obtain a three-dimensional geometric model of the hull and the processed data on the surrounding environment. After the processing is completed, a mathematical model of the hull motion is constructed by data simulation based on the three-dimensional geometric model of the hull and the processed data on the surrounding environment. Finally, a plan is made for the encounter and overtaking problems of two ships based on the mathematical model of the hull motion, and the hull is adjusted in real time by real-time auxiliary control based on the real-time perception of the surrounding environment during the operation, which improves the accuracy of the hull auxiliary control planning. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the process for analyzing and responding to ship-to-ship effects based on digital twin technology according to the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] In a specific embodiment of the present invention, Reference Figure 1As shown, this invention provides a method for analyzing and addressing ship-to-ship effects based on digital twin technology, including the following steps: S1. Install corresponding Internet of Things (IoT) devices around the hull, including: positioning sensors, cameras, and lidar; S2. Real-time collection of environmental data around the ship and ship data based on installed IoT devices; The data on the environment surrounding the hull includes: inter-ship force data and point cloud data of the environment surrounding the hull. S3. Process the environmental data around the ship and the ship data collected by the IoT device to obtain the three-dimensional geometric model of the ship and the processed environmental data around the ship. S4. Based on the three-dimensional geometric model of the hull and the processed environmental data around the hull, construct a mathematical model of hull motion through data simulation. S5. Based on the mathematical model of ship motion, plan the encounter and overtaking problems of two ships, and make real-time auxiliary control adjustments to the ship based on the real-time perception of the surrounding environment during the operation. Furthermore, referring to Figure 1 As shown, the real-time collection of environmental data and hull data based on installed IoT devices includes the following steps: S21. Divide the surrounding environment of the ship into grids to obtain the divided surrounding environment of the ship. Set the center coordinates of the area surrounding the ship's hull, and construct a coordinate system based on the set center coordinates; Furthermore, a unit distance is set for constructing the coordinate system, and the surrounding environment of the ship is divided based on the set unit distance to obtain the divided surrounding environment of the ship. S22. Set a data collection period based on the divided environmental area around the hull, and collect environmental data and hull data within the divided environmental area around the hull based on the set data collection period. Set data collection cycle set , Indicates the set number One collection cycle, Indicates the total number of set data collection cycles; Furthermore, a primary acquisition device and a backup acquisition device are set up; the primary acquisition device and the backup acquisition device are used to collect data on the surrounding environment and the ship data in the divided area around the ship hull, respectively, and a redundancy configuration is set between the primary acquisition device and the backup acquisition device. Furthermore, when the main acquisition device does not malfunction, the data acquisition cycle set is used as follows: The data on the surrounding environment and the ship itself collected by the main acquisition device are used as the real-time data on the surrounding environment and the ship itself. When the main acquisition device malfunctions, the environmental data around the ship and the ship data acquired by the main acquisition device will be used as the real-time environmental data around the ship and the ship data. Furthermore, referring to Figure 1 As shown, the process of processing the environmental data and hull data collected by IoT devices to obtain the hull's three-dimensional geometric model and the processed environmental data includes the following steps: S31. The collected environmental data around the ship is processed using data processing methods to obtain processed environmental data around the ship. S311. The collected data on the environment around the ship is standardized using a data standardization method to obtain standardized data on the environment around the ship. The standardization formula is as follows: ; in, This represents the minimum value of the environmental data surrounding the ship's hull. This represents the maximum value of the environmental data surrounding the ship's hull. This represents the collected data on the environment surrounding the ship's hull. This represents standardized data on the environment surrounding the ship's hull. S312. Based on the standardized environmental data surrounding the hull, perform positioning correction and target detection on the environmental data surrounding the hull. The standardized environmental data surrounding the ship's hull is defined as point cloud data. Using the lidar itself as the origin and the lidar's sensing range as the radius, the coordinate plane is divided into grids of fixed size. Point cloud pillars are constructed in conjunction with the Z-axis of the coordinate system. Each point cloud pillar contains several points. N is set as the number of points and D as the number of dimensions. Furthermore, the point cloud data acquired by the lidar is averaged by comparing multiple frames. The collected point cloud data is transmitted to a trained neural network for feature extraction. Based on the feature extraction, objects are identified and the feature points of the corresponding objects are saved. Furthermore, the coordinate position of the target object is determined based on the saved feature points and the constructed coordinate system. After determining the coordinate position, feature extraction is performed on another frame of point cloud data to obtain the new coordinate position, and it is compared with the feature points of the previous frame. If the overlap is higher than 80%, target detection is performed based on this. Furthermore, the point cloud data of adjacent frames are calculated using the mean algorithm, and the positioning correction of the environmental data around the ship is performed based on the mean calculation results. S32. The collected hull data is processed using 3D modeling methods to obtain a 3D geometric model of the hull. The collected ship hull data is stitched together using a target stitching method; Each area of ​​the ship's hull is numbered, and multiple monitoring points are set up in each area of ​​the ship's hull; Furthermore, three or more targets are placed in the public area between two adjacent monitoring points; Furthermore, the data and targets at each monitoring point are scanned sequentially using lidar and cameras; After the scan is completed, the data and targets in the non-monitoring points are stitched together to obtain a three-dimensional geometric model of the ship's hull. Furthermore, referring to Figure 1 As shown, based on the three-dimensional geometric model of the hull and the processed environmental data surrounding the hull, the mathematical model of the hull's motion is constructed through data simulation, including the following steps: The three-dimensional geometric model of the hull and the processed data of the surrounding environment of the hull are rasterized to determine the coordinates of the hull and the surrounding environment data in the raster network. Furthermore, a mathematical model of hull motion is constructed based on the coordinates of the hull and the surrounding environment data in the grid network determined within adjacent acquisition cycles. The ship's motion model is shown below: ; in, This represents the position coordinates of the ship's hull in the established coordinate system at time t. This represents the position coordinates of the ship's hull in the established coordinate system at time t-1. This represents the measurement data from the ship's hull monitoring equipment at time t. This represents the data of inter-ship force detected by the ship monitoring equipment at time t during the measurement process. Represents the equations of motion for the ship's hull. Indicates about and The equations of motion for the ship's hull; Furthermore, referring to Figure 1 As shown, the problem of two ships encountering and overtaking each other is planned based on the mathematical model of ship motion, and the real-time auxiliary control adjustment of the ship's hull is based on the real-time perception of the surrounding environment during the operation, including the following steps: The initial stage of a confrontation is defined as the bows of the two ships meeting, ending when the sterns of the two ships separate from contact; the starting point of the overtaking phenomenon is the intersection of the bow of the overtaking ship and the stern of the overtaken ship, ending when the stern of the overtaking ship surpasses the bow of the overtaken ship. The planning of the two-ship encounter and overtaking problem based on the mathematical model of ship motion includes the following steps: First, a three-dimensional geometric model of the ship's hull is constructed. After the geometric modeling is completed, the mathematical model of the ship's motion is used to calculate the ship's position coordinates in real time, while defining the calculation area for when the two ships meet. Furthermore, after defining the calculation area for the encounter between the two ships, the environmental data around the ship's hull is discretized into a grid; then, appropriate boundary constraints are configured, and a solver is used to perform numerical solutions to calculate the real-time auxiliary control parameters of the ship's hull. In one specific embodiment, the ship-to-ship effect analysis and response method based on digital twin technology further includes: a data acquisition module, a data processing module, a ship motion analysis module, and an auxiliary control module; The data acquisition module is used to collect real-time data on the surrounding environment and hull data. The data processing module is used to process the real-time collected data on the surrounding environment and the ship data to obtain a three-dimensional geometric model of the ship and the processed data on the surrounding environment. The hull motion analysis module is used to construct a mathematical model of hull motion through data simulation based on the three-dimensional geometric model of the hull and the processed data of the surrounding environment of the hull. The auxiliary control module is used to plan the encounter and overtaking problems of two ships based on the mathematical model of ship motion, and to make real-time auxiliary control adjustments to the ship based on the real-time perception of the surrounding environment during the operation.

[0019] It should be noted that The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A method for analyzing and mitigating inter-ship effects based on digital twin technology, characterized in that, Includes the following steps: S1. Install corresponding Internet of Things (IoT) devices around the hull, including: positioning sensors, cameras, and lidar; S2. Real-time collection of environmental data around the ship and ship data based on installed IoT devices; The data on the environment surrounding the hull includes: inter-ship force data and point cloud data of the environment surrounding the hull. S3. Process the environmental data around the ship and the ship data collected by the IoT device to obtain the three-dimensional geometric model of the ship and the processed environmental data around the ship. S4. Based on the three-dimensional geometric model of the hull and the processed environmental data around the hull, construct a mathematical model of hull motion through data simulation. The three-dimensional geometric model of the hull and the processed data of the surrounding environment of the hull are rasterized to determine the coordinates of the hull and the surrounding environment data in the raster network. A mathematical model of hull motion is constructed based on the coordinates of the hull and the surrounding environment data in the grid network determined within adjacent acquisition cycles. The ship's motion model is shown below: ； in, This represents the position coordinates of the ship's hull in the established coordinate system at time t. This represents the position coordinates of the ship's hull in the established coordinate system at time t-1. This represents the measurement data from the ship's hull monitoring equipment at time t. This represents the data of inter-ship force detected by the ship monitoring equipment at time t during the measurement process. Represents the equations of motion for the ship's hull. Indicates about and The equations of motion for the ship's hull; S5. Based on the mathematical model of ship motion, plan the encounter and overtaking problems of two ships, and make real-time auxiliary control adjustments to the ship based on the real-time perception of the surrounding environment during the operation. The initial stage of a confrontation is defined as the bows of the two ships meeting, ending when the sterns of the two ships separate from contact; the starting point of the overtaking phenomenon is the intersection of the bow of the overtaking ship and the stern of the overtaken ship, ending when the stern of the overtaking ship surpasses the bow of the overtaken ship. The planning of the two-ship encounter and overtaking problem based on the mathematical model of ship motion includes the following steps: First, a three-dimensional geometric model of the ship's hull is constructed. After the geometric modeling is completed, the mathematical model of the ship's motion is used to calculate the ship's position coordinates in real time, while defining the calculation area for when the two ships meet. After defining the calculation area for the encounter between the two ships, the environmental data around the ship's hull is discretized into a grid. Then, appropriate boundary constraints are configured, and a solver is used to perform numerical solutions to calculate the real-time auxiliary control parameters of the ship's hull.

2. The method for analyzing and responding to ship-to-ship effects based on digital twin technology according to claim 1, characterized in that, The real-time collection of environmental data and hull data based on the installed IoT devices includes the following steps: S21. Divide the surrounding environment of the ship into grids to obtain the divided surrounding environment of the ship. Set the center coordinates of the area surrounding the ship's hull, and construct a coordinate system based on the set center coordinates; Set the unit distance for constructing the coordinate system, and divide the surrounding environment area of ​​the ship based on the set unit distance to obtain the divided surrounding environment area of ​​the ship. S22. Set a data collection period based on the divided environmental area around the hull, and collect environmental data and hull data within the divided environmental area around the hull based on the set data collection period.

3. The method for analyzing and responding to ship-to-ship effects based on digital twin technology according to claim 2, characterized in that, The process of setting a data collection period based on the divided environmental area surrounding the hull, and collecting environmental data and hull data within the divided environmental area based on the set data collection period, includes the following steps: Set data collection cycle set , Indicates the set number One collection cycle, Indicates the total number of set data collection cycles; Set up a primary acquisition device and a backup acquisition device; use the primary acquisition device and the backup acquisition device to collect data on the surrounding environment and the ship itself within the divided area of ​​the surrounding environment, and set up redundancy between the primary acquisition device and the backup acquisition device. When the main acquisition device is not malfunctioning, according to the data acquisition cycle set The data on the surrounding environment and the ship itself collected by the main acquisition device are used as the real-time data on the surrounding environment and the ship itself. When the main acquisition device malfunctions, the environmental data around the ship and the ship data collected by the main acquisition device will be used as the real-time environmental data around the ship and the ship data.

4. The method for analyzing and responding to ship-to-ship effects based on digital twin technology according to claim 1, characterized in that, The process of processing the environmental data around the ship and the ship data collected by the Internet of Things devices to obtain the three-dimensional geometric model of the ship and the processed environmental data around the ship includes the following steps: S31. The collected environmental data around the ship is processed using data processing methods to obtain processed environmental data around the ship. S32. The collected hull data is processed using 3D modeling methods to obtain a 3D geometric model of the hull.

5. The method for analyzing and responding to ship-to-ship effects based on digital twin technology according to claim 4, characterized in that, The process of processing the collected environmental data around the ship using data processing methods to obtain processed environmental data around the ship includes the following steps: S311. The collected data on the environment around the ship is standardized using a data standardization method to obtain standardized data on the environment around the ship. The standardization formula is as follows: ； in, This represents the minimum value of the environmental data surrounding the ship's hull. This represents the maximum value of the environmental data surrounding the ship's hull. This represents the collected data on the environment surrounding the ship's hull. This represents standardized data on the environment surrounding the ship's hull. S312. Based on the standardized environmental data surrounding the hull, perform positioning correction and target detection on the environmental data surrounding the hull.

6. The method for analyzing and responding to ship-to-ship effects based on digital twin technology according to claim 5, characterized in that, The process of positioning correction and target detection based on standardized ship surrounding environment data includes the following steps: The standardized environmental data surrounding the ship's hull is defined as point cloud data. Using the lidar itself as the origin and the lidar's sensing range as the radius, the coordinate plane is divided into grids of fixed size. Point cloud pillars are constructed in conjunction with the Z-axis of the coordinate system. Each point cloud pillar contains several points. N is set as the number of points and D as the number of dimensions. The point cloud data acquired by the lidar is averaged by comparing multiple frames. The collected point cloud data is transmitted to a trained neural network for feature extraction. Based on the feature extraction, objects are identified and the feature points of the corresponding objects are saved. The coordinate position of the target object is determined based on the saved feature points and the constructed coordinate system. After the coordinate position is determined, feature extraction is performed on another frame of point cloud data to obtain the new coordinate position, and it is compared with the feature points of the previous frame. If the overlap is higher than 80%, the target detection is performed based on this. The point cloud data of adjacent frames are calculated using the mean algorithm, and the location correction of the surrounding environment data of the ship is performed based on the mean calculation results.

7. The method for analyzing and responding to ship-to-ship effects based on digital twin technology according to claim 4, characterized in that, The process of processing the collected hull data using 3D modeling methods to obtain a 3D geometric model of the hull includes the following steps: The collected ship hull data is stitched together using a target stitching method; Each area of ​​the ship's hull is numbered, and multiple monitoring points are set up in each area of ​​the ship's hull; Place three or more targets in the common area between two adjacent monitoring points; The data and targets at each monitoring point are scanned sequentially using lidar and cameras; After the scan is completed, the data and targets from the non-monitoring points are stitched together to obtain a three-dimensional geometric model of the ship's hull.

8. A method for analyzing and responding to ship-to-ship effects based on digital twin technology as described in any one of claims 1-7, characterized in that, Also includes: Data acquisition module, data processing module, hull motion analysis module, and auxiliary control module; The data acquisition module is used to collect real-time data on the surrounding environment and hull data. The data processing module is used to process the real-time collected data on the surrounding environment and the ship data to obtain a three-dimensional geometric model of the ship and the processed data on the surrounding environment. The hull motion analysis module is used to construct a mathematical model of hull motion through data simulation based on the three-dimensional geometric model of the hull and the processed data of the surrounding environment of the hull. The auxiliary control module is used to plan the encounter and overtaking problems of two ships based on the mathematical model of ship motion, and to make real-time auxiliary control adjustments to the ship based on the real-time perception of the surrounding environment during the operation.

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