A floating body floatation simulation still water draft system, method and apparatus

Abstract

The present application relates to the technical field of water floating body dynamic floating state simulation, and particularly relates to a floating body floating state simulation static draft reduction system, method and device. The system comprises a data acquisition module, a data processing and reasoning module, a static draft reduction and optimization module and a result display module. The data acquisition module is used for collecting real-time relevant data such as dynamic draft of the ship body. The data processing and reasoning module is connected with the data acquisition module and constructs a cause-effect relationship matrix. The static draft reduction and optimization module is used for receiving analysis results of the data processing and reasoning module and restoring quantifiable dynamic draft mapping relationship. The result display module is used for receiving and displaying results of the static draft reduction and optimization module. Through cause-effect reasoning and parameter calculation, the present application can correct dynamic compensation in real time, including the influence of interference factors such as environment, speed and load changes, and can realize a visual interface of static draft of the ship or floating body to accurately analyze and monitor the change of the center of gravity of the ship mass.

Description

Technical Field

[0001] This invention relates to the field of dynamic buoyancy simulation technology, and in particular to a system, method and apparatus for simulating and restoring static draft of a floating body. Background Technology

[0002] Vessels or floating bodies on water are constantly in a dynamic environment. Whether moored, sailing, or anchored, the hull is affected by internal and external factors such as wind, waves, currents, its own speed, and load movement, causing changes in attitude such as pitching and shifting of the center of gravity. Changes in the draft and attitude of the vessel or floating body are difficult to control and perceive. Current technologies for obtaining the ship's floating state mainly rely on liquid level sensors in the ship's liquid tanks, calculating the static floating state based on the factory loading manual. This does not consider the combined effects of changes in the state after leaving the factory, resulting in large deviations in reconstructing the static draft, an unintuitive floating state, and the inability to coordinate real-time draft data across systems. However, mastering the ship's static pitch and roll floating state data is fundamental to the evaluation and analysis of the ship's resistance performance during navigation. If the floating state of the ship or floating body, especially the ship's pitch and roll attitude, is inaccurate, it will adversely affect the ship's navigation energy efficiency analysis and hull safety analysis.

[0003] Ship draft is affected by weather, speed, and center of gravity shifts. Existing methods cannot accurately and in real time determine a ship's static floating state. Current technologies lack a comprehensive consideration of the combined effects of various factors, including ship characteristic parameters, mass load changes, speed characteristics, and hydrodynamic characteristics. Therefore, it is impossible to accurately simulate the ship's attitude in the trim direction under the combined influence of these factors, or to precisely analyze the dynamic-to-static attitude changes and influencing factors in water. Thus, there is an urgent need for a method and device capable of real-time sensing of a ship's static floating state to achieve economical navigation, assess the risks of abnormal load changes, and ensure the ship's safety. Summary of the Invention

[0004] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this invention provides a floating body floating state simulation and restoration static draft system, method, and apparatus, which realizes causal reasoning and parameter calculation, real-time correction and dynamic compensation, including the interference effects of environmental, speed, and load changes, and can realize a visual interface for the static draft of ships or floating bodies to analyze the safety of changes in the ship's center of gravity.

[0005] This invention provides a floating body buoyancy simulation and static draft restoration system, comprising: a data acquisition module, a data processing and inference module, a static draft restoration and optimization module, and a result display module.

[0006] The data acquisition module is used to collect dynamic data of the ship's hull;

[0007] The data processing and reasoning module is used to calculate causal relationship coefficients and determine causal relationship equations based on relevant data such as the dynamic draft of the ship.

[0008] The static draft restoration and optimization module is used to establish a static draft inversion estimation equation for the ship based on the causal relationship coefficient, and calculate the restored static draft value.

[0009] The result display module is used to receive and display the restored static draft value.

[0010] According to the present invention, a floating body floating state simulation and static draft restoration system is provided, wherein the data acquisition module includes: a hull dynamic attitude measurement unit, a sea wave sensor unit, a hull characteristic parameter sensing unit, a speed sensor unit, and a ship load change measurement unit.

[0011] According to the floating state simulation and static draft restoration system of the present invention, the workflow of the data processing and inference module is as follows:

[0012] S11: Extract feature data from the dynamic data collected by the data acquisition module;

[0013] S12: Determine path coefficients through fusion training based on ship hydrodynamic mechanisms and deep structural equation models;

[0014] S13: Construct a deep structural equation based on the feature data and path coefficients;

[0015] S14: Based on the path coefficients, deep structural equations, and feature data, calculate the causal relationship coefficients and determine the causal relationship equation.

[0016] According to the present invention, a floating body buoyancy simulation and static draft restoration system is provided, wherein the depth structure equation is:

[0017]

[0018] in, This is the matrix representing the total dynamic draft change of the ship. For path coefficients, For data on the characteristics of ship draft changes, This is a constant bias term.

[0019] According to the present invention, a floating body buoyancy simulation system for restoring static draft is provided, wherein the causal relationship correlation equation is:

[0020]

[0021] in, This is the matrix representing the total dynamic draft change of the ship. For ship speed, For wave height, Given the known change in load, For the length of the ship, It is the acceleration due to gravity. P The distance from the center of the float to the perpendicular from the bow. Given the longitudinal distance moved by the known load change, The moment of tilt per centimeter, For speed influence coefficient, The wave influence coefficient is... Given the known load movement influence coefficient, The coefficient representing the influence of the coupling error between the ship's environment and speed. This is the error term caused by the coupling of ship environmental factors and speed; among which, , , and This is the causal relationship coefficient.

[0022] According to the present invention, a floating body floating state simulation and static draft restoration system is provided, wherein the static draft restoration and optimization module has the following inversion equation for ship static draft:

[0023]

[0024] in, d To restore the static draft value, D This refers to the actual dynamic draft of the ship's trim.

[0025] According to the present invention, a floating body floating state simulation and static draft restoration system is provided. The floating body floating state simulation and static draft restoration system is deployed at the edge end of the ship to measure the actual dynamic draft of the ship's trim, and calculates the restored static draft based on the actual dynamic draft of the ship's trim and the ship's static draft inversion estimation equation.

[0026] The present invention also provides a method for simulating the static draft of a floating body, comprising the following steps:

[0027] S100: Uses a data acquisition module to collect dynamic data of the hull;

[0028] S200: The data acquisition module inputs dynamic data into the data processing and reasoning module to obtain causal relationship coefficients and causal relationship equations. The data processing and reasoning module inputs the causal relationship coefficients into the static draft restoration and optimization module to obtain the restored static draft value.

[0029] S300: The result display module displays the restored static draft value on the screen.

[0030] The present invention also provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor is used to execute the program to implement the steps of the floating state simulation and static draft restoration method of a floating body as described above.

[0031] The present invention provides a floating body buoyancy simulation and static draft restoration system, method, and apparatus, which overcomes the shortcomings of the prior art and realizes the simulation and monitoring of dynamic draft of ships to restore static draft, and has the following advantages:

[0032] 1. This invention uses ship hydrodynamics mathematics, integrating dynamic-static mapping algorithms and deep structural equation model training, to improve the accuracy of dynamic reconstruction of static floating state calculations of ships or floating bodies, meet the requirements for resistance performance evaluation during ship navigation, and improve the applicability and safety of ships in dynamic marine environments.

[0033] 2. By comprehensively considering various factors such as ship parameters, weather and wave effects, ship load variation characteristics, and ship speed characteristics, the static draft generation mechanism is generated through deep structural causal analysis, which can simulate the static attitude of the ship in the water in all factors; the two-stage restoration framework of "causal inference + environmental compensation optimization" improves the simulation accuracy.

[0034] 3. Using a specific algorithm, the system performs a weighted analysis on each factor affecting the ship's floating state, and removes the influence of load movement, speed, and wind and wave interference one by one, allowing the ship to gradually return to a static equilibrium floating state. This allows operators to adjust and optimize the system parameters according to actual needs.

[0035] 4. The updated static floating state data and data on various influencing factors can be restored in real time and displayed on the screen in graphical or data form. The visual interface intuitively reflects the changes in the ship's dynamic to static attitude.

[0036] 5. This technology is used to assess and analyze unexpected changes in the load mass of a ship's floating body, to warn of risks such as unexpected movement of heavy cargo or unexpected water ingress into the hull under dynamic environmental conditions, and to send warning signals to other systems of the ship.

[0037] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in this 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 some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of a floating body buoyancy simulation and static draft restoration system provided by the present invention.

[0040] Figure 2 This is a flowchart of a method for simulating the static draft of a floating body using floating state simulation, provided by the present invention.

[0041] Figure 3 This is a schematic diagram of the electronic device provided by the present invention.

[0042] Figure label:

[0043] 101. Data acquisition module; 102. Data processing and inference module; 103. Static draft restoration and optimization module; 104. Result display module; 810. Processor; 820. Communication interface; 830. Memory; 840. Communication bus. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention. The following embodiments are used to illustrate this invention but cannot be used to limit the scope of this invention.

[0045] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0046] The following is combined with Figures 1 to 3 This invention is described.

[0047] Example

[0048] like Figure 1 As shown, Figure 1This invention provides a structural schematic diagram of a floating body buoyancy simulation and static draft restoration system. It includes: a data acquisition module 101, a data processing and inference module 102, a static draft restoration and optimization module 103, and a result display module 104.

[0049] The data acquisition module 101 is used to collect relevant data such as the dynamic draft of the ship's hull;

[0050] The data processing and reasoning module 102 is used to calculate and obtain causal relationship coefficients based on relevant data such as the dynamic draft of the ship's hull, and to determine the causal relationship equation.

[0051] The static draft restoration and optimization module 103 is used to receive causal relationship coefficients, establish a ship static draft inversion estimation equation based on the causal relationship coefficients, and calculate the restored static draft value.

[0052] The result display module 104 is used to receive and display the restored static draft value.

[0053] Specifically, the data acquisition module 101 consists of multiple sets of ship sensing units, including: a ship dynamic attitude measurement unit, a sea wave sensor unit, a ship characteristic parameter sensing unit, a speed sensor unit, and a ship load change measurement unit.

[0054] The ship dynamic attitude measurement unit acquires real-time ship dynamic attitude and consists of draft measurement sensors located at multiple positions on the hull and an attitude reference unit (MRU). The draft measurement sensors measure dynamic draft data at four or more points on each side of the bow, midships, and stern, and calculate the average draft over a certain period. The attitude reference unit continuously collects total pitch angle data over a period and calculates its arithmetic mean to obtain the average heel angle. The ship attitude measurement unit obtains real-time dynamic draft data from the acquired average draft and heel angle.

[0055] The marine wave sensor unit acquires wave data of the ship's location through sensors, including measuring wave parameters such as wave height, wave period, and wave direction.

[0056] The ship characteristic parameter sensing unit obtains parameters corresponding to different loading capacities of the ship, including the ship's main dimensions, MTC and displacement, through the ship design specifications and hydrostatic tables, and calculates the changes in the center of gravity and center of buoyancy of the ship caused by the loading due to mid-arching or mid-sag, and obtains the ship's characteristic parameters.

[0057] The speed sensor unit senses the ship's speed information through the ship's GPS and Beidou systems.

[0058] The ship load mass change measurement unit can calculate known load mass changes and center of gravity position changes through data. After a ship or floating body has been sailing or operating for a certain period of time, it can calculate the changes in ship load mass caused by oil and water consumption and ballast water allocation based on real-time consumption of ship fuel, fresh water and other oil and water and ballast water adjustment records.

[0059] Specifically, the workflow of the data processing and reasoning module 102 is as follows:

[0060] S11: Extract feature data from the dynamic draft and other related data collected by the data acquisition module 101. Specifically, the feature data includes known load changes, hull characteristic changes, speed changes, wind and wave changes, and other feature data.

[0061] S12: Path coefficients are determined through fusion training based on ship hydrodynamic mechanisms and deep structural equation model. A large amount of ship navigation data and environmental data under different operating conditions are collected using ship hydrodynamic mechanisms, including wind and wave environment information, speed, fuel and water consumption changes, and corresponding dynamic attitude and draft data. A model is established, and deep structural equation modeling is performed on the dynamic draft generated by the independent variable set under different operating conditions. The ship hydrodynamic mechanisms and deep structural equation model are then fused and trained to determine the path coefficients. The determination of path coefficients provides data basis for the subsequent static draft restoration algorithm, and can intuitively display the weight of each characteristic influencing factor.

[0062] S13: Construct a deep structural equation based on the feature data and path coefficients.

[0063] S14: Based on the path coefficients, deep structural equations, and feature data, calculate the causal relationship coefficients and determine the causal relationship equation.

[0064] Deep Structural Equation Modeling (Deep SEM) is both an evolution of structural equation modeling and an application of machine learning, particularly deep learning, to specific modeling tasks. Therefore, it crosses the boundaries between traditional econometric modeling and machine learning, and can be considered an important branch of machine learning applications in causal inference and latent variable modeling. The scope of application for Deep SEM includes: maintaining traditional linear / nonlinear regression forms for causal relationships (path models) between latent variables, and using neural network methods to model more complex nonlinear relationships.

[0065] Specifically, the depth structure equation is:

[0066]

[0067] in, The total dynamic draft change matrix of the ship is the second potential variable. For path coefficients, The data on changes in ship draft are the first latent variable. This is a constant bias term. The characteristic data includes known load changes, hull characteristic changes, speed changes, wind and wave changes, etc. The total draft change is obtained by superimposing all the data. The path coefficient represents the strength and direction of the causal relationship between the dynamic draft and the latent variables.

[0068] Specifically, a nonlinear mapping relationship is established between the influence of each characteristic factor on dynamic draft and dynamic draft changes. The causal relationship matrix and causal correlation equation are combined with ship hydrodynamic environment compensation technology to calculate the causal correlation equation:

[0069]

[0070] in, For ship speed, For wave height, Given the known change in load, For the length of the ship, It is the acceleration due to gravity. P The distance from the center of the float to the perpendicular from the bow. Given the longitudinal distance moved by the known load change, The moment of tilt per centimeter, For speed influence coefficient, The wave influence coefficient is... Given the known load movement influence coefficient, The coefficient representing the influence of the coupling error between the ship's environment and speed. This is the error term caused by the coupling of ship environmental factors and speed, among others. , , and These are causal coefficients, derived from the path coefficients corresponding to the deep structural equations.

[0071] The causal relationship equations include the speed influence term, wave influence term, load movement influence term, and ship environment and speed coupling term.

[0072] Speed ​​Influence Term: The Froude number in hydrodynamics represents the direct relationship between speed and draft. That is, the Froude number and draft are correlated in a dimensionless manner, linking speed with draft and ship length. According to the Froude number formula, the dynamic change in a ship's draft is proportional to the Froude number, expressed as:

[0073]

[0074] in, This is a factor affecting speed.

[0075] Wave influence term: Based on the second-order wave force response model in the wave load theory, i.e. the second-order potential flow theory, the heave and pitch motion caused by the wave, i.e. the dynamic draft, is proportional to the square of the wave height.

[0076]

[0077] in, This refers to the impact of wind and waves.

[0078] Load movement effect: This is derived from the mechanism by which the ship's moment of inertia reflects the influence of the center of gravity position on stability. The mechanism by which a shift in the center of gravity exacerbates pitching, thus leading to dynamic changes in draft, is as follows:

[0079]

[0080] in, This is the load movement effect term.

[0081] Ship environment and speed coupling term: The combined effect of ship speed and waves may amplify the ship's motion response. The influence of the coupling term on the path coefficient is calibrated using experimental data.

[0082]

[0083] in, This is a coupling term between the ship's environment and speed.

[0084] When analyzing the weights, the entire deep structural equation model is jointly trained using the stochastic gradient descent method of a neural network. The resulting "weight coefficients" typically refer to standardized path coefficients, which represent how many standard deviations the dynamic draft changes when a given independent variable changes by one standard deviation. For example, after experimental training and convergence, the following standardized estimates were obtained for a certain case, as shown in Table 1:

[0085] Table 1 Weight Calculation Estimation Table

[0086]

[0087] Standardized coefficient = Unstandardized coefficient × Dependent variable standard deviation / Independent variable standard deviation

[0088] The standardized coefficients are weighted coefficients, representing the degree of contribution of each factor to the dynamic draft change, and the analysis is as follows:

[0089] Load movement impact (weight 0.60): Highest weight. This indicates that for this ship, center of gravity shift (potentially due to improper cargo stowage or free surface effect) is the most significant factor causing dynamic draft changes. This means that the ship is extremely sensitive to draft changes once it tilts during navigation.

[0090] Wave influence (weight 0.52): The second highest weight. This indicates that sea state (wave height) has a significant impact on dynamic draft, and heave motion significantly increases the peak draft.

[0091] The coupling term between ship environment and speed (weight 0.50) is significant. This verifies the existence of nonlinear interaction effects. If the coupling term is ignored and only linear superposition is used, the model's prediction error for dynamic draft will be large. This high weight indicates that when high speed, large waves, and drift occur simultaneously, a resonance effect of "1+1>2" is produced.

[0092] Speed ​​impact (weight 0.30): This has the lowest relative weight. It indicates that within the current range of speed variation, the change in sinking caused by speed changes is less than the impact of wind, waves, and drift.

[0093] Therefore, by calculating the dynamic draft in real time, the current environmental parameters and the ship's status are input into a pre-trained LSTM neural network. This network serves as a measurement model to extract the dynamic draft potential variable and estimate its factor weight loading with the observed variable.

[0094] Specifically, the static draft is estimated by using the difference between the dynamic draft data obtained from actual experiments and the total dynamic draft change calculated by the model as a correction factor, thus reconstructing the static draft attitude model:

[0095]

[0096] in, d D represents the static draft value to be restored, while D represents the actual dynamic draft value of the ship's trim.

[0097] If the restored static draft of the hull or floating body exceeds a certain threshold of the baseline static draft, it indicates a risk of hull damage or accidental movement of the ship's internal load / cargo, even without a change in the ship's mass. This can output a safety warning signal, triggering the safety warning of the ship's static draft restoration system. This device learns hull damage characteristics from data through a deep learning model, restores static draft data information, and precisely controls the hull damage threshold setting, which is beneficial for analyzing the safety of changes in the ship's center of gravity.

[0098] Specifically, the floating body floating state simulation and static draft restoration system is deployed at the edge of the ship to measure the actual dynamic draft of the ship's trim and to calculate the restored static draft based on the actual dynamic draft of the ship's trim and the ship's static draft inversion estimation equation.

[0099] Furthermore, embodiments of the present invention can also optimize the static draft attitude model based on actual experimental parameters.

[0100] Time optimization of project parameters: The method combines the dynamic reconstruction of static draft of the ship. The characteristic data has the characteristic of time lag in the impact of draft. The lag time variable is introduced. The real-time data reflects the dynamic draft change time relationship, and the parameter time is optimized.

[0101] Optimization of project error values: After acquiring real-time dynamic draft data of the ship, the static draft data calculated and restored using this method is compared with the actual measured static draft data, the error term is calculated, and the parameters of the mapping relationship are adjusted to improve the accuracy of static draft restoration.

[0102] Specifically, the ship trim and buoyancy restoration device is deployed at the edge of the ship to construct a dynamic draft restoration static draft simulation device, realize real-time calculation of data processing at the edge, evaluate the ship's static buoyancy information from the restored static draft value, average trim angle and ship characteristic parameters, and the generated signal can be transmitted to the outside system at the edge.

[0103] Specifically, the result display module 104 generates ship static floating state information based on the static draft restoration results. The display module refines the ship static floating body information based on the evaluation of the ship's static floating state, including the ship's restored static draft parameter information, generating static floating body visualization data charts, and simulating the ship's static draft visualization 3D graphics, feature influence item influence coefficients, which are used to display the ship's real-time static draft status and influencing factors, and complete the on-site quick query and analysis function of the ship's or floating body's static draft.

[0104] The embodiments of the present invention employ an adversarial training enhancement mode to train generalization capabilities under different sea conditions, and verify the data collected and the model optimized by providing a 1-second dynamic draft update.

[0105] In the static water regression test, the model output was compared with the measured values ​​of the laser rangefinder. The calculated mean absolute error (MAE) was less than 2 cm, meeting the requirements for judging the pitch of the floating body during ship navigation. The static draft restoration error was reduced by more than 75% compared with traditional methods.

[0106] This invention compares the traditional table lookup method with the traditional method to calculate the draft changes of the same vessel. Specific experimental data are shown in Table 2:

[0107] Table 2 Comparison of Optimized Ship Draft Experiment Data

[0108]

[0109] As shown in Table 2, it can be seen that the present invention has significant improvements over the traditional method.

[0110] This invention overcomes the shortcomings of existing technologies and realizes the simulation and monitoring of the dynamic draft of ships to restore their static draft, and has the following advantages:

[0111] 1. The technology uses ship hydrodynamics mathematics, integrating dynamic-static mapping algorithms and deep structural equation model training to improve the accuracy of dynamic reconstruction of static floating state calculations of ships or floating bodies, meet the requirements for resistance performance evaluation during ship navigation, and improve the applicability and safety of ships in dynamic marine environments.

[0112] 2. By comprehensively considering various factors such as ship parameters, weather and wave effects, ship load variation characteristics, and ship speed characteristics, the static draft generation mechanism is generated through deep structural causal analysis, which can simulate the static attitude of the ship in the water in all factors; the two-stage restoration framework of "causal inference + environmental compensation optimization" improves the simulation accuracy.

[0113] 3. Using a specific algorithm, the system performs a weighted analysis on each factor affecting the ship's floating state, and removes the influence of load movement, speed, and wind and wave interference one by one, allowing the ship to gradually return to a static equilibrium floating state. This allows operators to adjust and optimize the system parameters according to actual needs.

[0114] 4. The updated static floating state data and data on various influencing factors can be restored in real time and displayed on the screen in graphical or data form. The visual interface intuitively reflects the changes in the ship's dynamic to static attitude.

[0115] 5. This technology is used to qualitatively assess unexpected changes in the load mass of a ship's floating body, to warn of risks such as unexpected movement of heavy cargo or unexpected water ingress into the hull under dynamic environmental conditions, and to send warning signals to other systems of the ship.

[0116] like Figure 2 As shown, Figure 2 This is a flowchart of a method for simulating the static draft of a floating body using floating state simulation, provided by the present invention, including the following steps:

[0117] S100: Uses a data acquisition module to collect dynamic data of the hull;

[0118] S200: The data acquisition module inputs dynamic data into the data processing and reasoning module to obtain causal relationship coefficients and causal relationship equations. The data processing and reasoning module inputs the causal relationship coefficients into the static draft restoration and optimization module to obtain the restored static draft value.

[0119] S300: The result display module displays the restored static draft value on the screen.

[0120] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840. The processor 810, communication interface 820, and memory 830 communicate with each other via the communication bus 840. The processor 810 can call logical instructions stored in the memory 830. The processor 810 is used for process handling in the floating state simulation and restoration of static draft method. The memory 830 is used for storing acquired data. The communication interface 820 is used for communication with the data acquisition module. The communication bus 840 is further connected to a display for visualizing the dynamic to static attitude changes of the ship, in order to execute a floating state simulation and restoration of static draft method, which includes:

[0121] S100: Uses a data acquisition module to collect dynamic data of the hull;

[0122] S200: The data acquisition module inputs dynamic data into the data processing and reasoning module to obtain causal relationship coefficients, and the data processing and reasoning module inputs the causal relationship coefficients into the static draft restoration and optimization module to obtain the restored static draft value;

[0123] S300: The result display module displays the restored static draft value on the screen.

[0124] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0125] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0126] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0128] It should be noted that the embodiments of this disclosure can be implemented using hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by a suitable instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the above-described devices and methods can be implemented using computer-executable instructions and / or included in processor control code, for example, such code provided on a programmable memory or a data carrier such as an optical or electronic signal carrier.

[0129] Furthermore, although the operation of the methods of this disclosure is described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Rather, the steps depicted in the flowcharts may be performed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps. It should also be noted that the features and functions of two or more devices according to this disclosure may be embodied in one device. Conversely, the features and functions of one device described above may be further divided and embodied by multiple devices.

[0130] While this disclosure has been described with reference to several specific embodiments, it should be understood that this disclosure is not limited to the specific embodiments disclosed. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A floating body buoyancy simulation and static draft restoration system, characterized in that, include: Data acquisition module, data processing and inference module, static draft restoration and optimization module, and result display module: The data acquisition module is used to collect dynamic data of the ship's hull; The data processing and reasoning module is used to calculate causal relationship coefficients and determine causal relationship equations based on the ship's dynamic draft data. The workflow of the data processing and reasoning module is as follows: S11: Extract feature data from the dynamic data collected by the data acquisition module; S12: Determine path coefficients through fusion training based on ship hydrodynamic mechanisms and deep structural equation models; S13: Construct a deep structural equation based on the feature data and path coefficients; S14: Based on the path coefficients, deep structural equations, and feature data, calculate the causal relationship coefficients and determine the causal relationship equation; the causal relationship equation is: in, This is the matrix representing the total dynamic draft change of the ship. For ship speed, For wave height, Given the known change in load, For the length of the ship, It is the acceleration due to gravity. P The distance from the center of the float to the perpendicular from the bow. Given the longitudinal distance moved by the known load change, The moment of tilt per centimeter, For speed influence coefficient, The wave influence coefficient is... Given the known load movement influence coefficient, The coefficient representing the influence of the coupling error between the ship's environment and speed. This is the error term caused by the coupling of ship environmental factors and speed. in, , , and The coefficient represents the causal relationship. The static draft restoration and optimization module is used to establish a static draft inversion estimation equation for the ship based on the causal relationship coefficient, and calculate the restored static draft value. The result display module is used to receive and display the restored static draft value.

2. The floating state simulation and static draft restoration system for a floating body according to claim 1, characterized in that, The data acquisition module includes: a hull dynamic attitude measurement unit, a sea wave sensor unit, a hull characteristic parameter sensing unit, a speed sensor unit, and a ship load change measurement unit.

3. The floating state simulation and static draft restoration system for a floating body according to claim 1, characterized in that, The depth structure equation is: in, This is the matrix representing the total dynamic draft change of the ship. For path coefficients, For data on the characteristics of ship draft changes, This is a constant bias term.

4. The floating state simulation and static draft restoration system for a floating body according to claim 1, characterized in that, The static draft restoration and optimization module's inversion equation for ship static draft is as follows: in, d To restore the static draft value, D This refers to the actual dynamic draft of the ship's trim.

5. The floating state simulation and static draft restoration system for a floating body according to claim 1, characterized in that, The floating body floating state simulation and static draft restoration system is deployed at the edge of the ship to measure the actual dynamic draft of the ship's trim, and calculates the restored static draft based on the actual dynamic draft of the ship's trim and the ship's static draft inversion estimation equation.

6. A method for simulating and restoring static draft of a floating body, used to execute a system for simulating and restoring static draft of a floating body as described in any one of claims 1 to 5, characterized in that, Includes the following steps: S100: Uses a data acquisition module to collect dynamic data of the hull; S200: The data acquisition module inputs dynamic data into the data processing and reasoning module to obtain causal relationship coefficients and causal relationship equations. The data processing and reasoning module inputs the causal relationship coefficients into the static draft restoration and optimization module to obtain the restored static draft value. S300: The result display module displays the restored static draft value on the screen.

7. An electronic device comprising a processor, a communication interface, a memory, and a communication bus, characterized in that, When the processor executes the computer program, it implements the steps of the floating state simulation and static draft restoration method for a floating body as described in claim 6.

Images