Ship control motion simple mechanism modeling method and system

Abstract

The invention belongs to the technical field of ship control motion identification modeling, and particularly discloses a simple mechanism modeling method and system for ship control motion, and the method comprises the steps: inputting motion state data at different rudder angles into a ship control motion model; correlation among different hydrodynamic derivatives in the longitudinal movement direction, the transverse movement direction and the bow turning movement direction is calculated, and hydrodynamic derivatives with correlation coefficients exceeding a preset coefficient are combined into a group; adjusting the grouped hydrodynamic derivatives according to a certain proportion, obtaining multiple manipulation motion numerical simulation, calculating total sensitivity values of the hydrodynamic derivatives relative to motion in a ship horizontal plane in different proportions, merging the hydrodynamic derivatives corresponding to the total sensitivity values greater than a preset sensitivity value, and completing simplification of a ship manipulation motion model. And forming a simple mechanism model of ship control movement. The simple mechanism model provided by the invention shows excellent forecasting performance and generalization ability.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of ship maneuvering motion identification modeling, and more particularly, relates to a ship maneuvering motion simple mechanism modeling method and system. BACKGROUND

[0002] Traditional ship maneuvering motion models usually contain a large number of hydrodynamic derivatives. Although these derivatives can improve the nonlinear expression ability of the model, they significantly increase the complexity and redundancy of the model. This not only puts higher requirements on the performance of the identification algorithm, but also puts stringent requirements on the richness of the dynamics information contained in the training data. In actual engineering applications, it is often difficult to obtain comprehensive and high-quality training data, especially in the design of new ships and complex sea conditions.

[0003] In the prior art, although there are some ship maneuvering motion modeling methods, these methods mostly have the following limitations: (1) High model complexity: contains a large number of hydrodynamic derivatives, resulting in complex model structure and large amount of calculation, and high requirements on the performance of the identification algorithm. (2) Strong data dependence: a large amount of training data is required to accurately identify model parameters, and in actual applications, it is often difficult to obtain large-scale high-quality training data. (3) Poor generalization ability: when the data is insufficient or the linear characteristics dominate in the data, the prediction accuracy and stability of the model are poor, making it difficult to adapt to different ship maneuvering motion scenarios. (4) In addition, when using standard Z-shaped test data for identification modeling, the fixed amplitude periodic rudder angle input is difficult to fully excite the nonlinear dynamics characteristics of the ship, resulting in insufficient identification accuracy of high-order hydrodynamic derivatives, and serious parameter drift phenomenon, thereby reducing the stability and reliability of the identification modeling. SUMMARY

[0004] In view of the defects of the prior art, the purpose of the present application is to provide a ship maneuvering motion simple mechanism modeling method and system, which aims to solve the problems of high model complexity in existing ship maneuvering motion modeling methods, and due to the fixed amplitude periodic rudder angle input, it is difficult to fully excite the nonlinear dynamics characteristics of the ship, resulting in insufficient identification accuracy of high-order hydrodynamic derivatives, and serious parameter drift phenomenon, thereby reducing the stability and reliability of the identification modeling.

[0005] To achieve the above purpose, in a first aspect, the present application provides a ship maneuvering motion simple mechanism modeling method, which simplifies the hydrodynamic derivatives through correlation and sensitivity dual coupling analysis, and specifically includes the following steps: The motion state data under different rudder angles are input into the ship maneuvering motion model. The correlation between different hydrodynamic derivatives in the longitudinal, lateral and bow-turning directions is calculated respectively. Hydrodynamic derivatives with correlation coefficients exceeding the preset coefficient are merged into a group. The hydrodynamic derivatives after grouping are adjusted according to a certain ratio. Numerical simulations of multiple maneuvering motions are obtained. The overall sensitivity value of the hydrodynamic derivatives relative to the ship's motion in the horizontal plane is calculated at different ratios. Hydrodynamic derivatives with an overall sensitivity value greater than the preset sensitivity value are merged to simplify the ship maneuvering motion model and form a simplified mechanism model of ship maneuvering motion.

[0006] More preferably, the correlation coefficient between different hydrodynamic derivatives is calculated using the Spearman correlation coefficient method. The Spearman correlation coefficient is:

[0007] in, For the first hydrodynamic derivative corresponding to the first i Group motion state data; For the second hydrodynamic derivative corresponding to the first i Group motion state data; The mean of all motion state data corresponding to the first hydrodynamic derivative; This is the mean of all motion state data corresponding to the second hydrodynamic derivative.

[0008] More preferably, the overall sensitivity value of the hydrodynamic derivative to the ship's motion in the horizontal plane is:

[0009] in, k The first numerical simulation representing the manipulation motion k Group data; N The total amount of data used in the numerical simulation of manipulating motion; For the first time without adjusting the hydrodynamic derivative k Group longitudinal velocity; To adjust the first j When the hydrodynamic derivative ratio is 1, the first k Group longitudinal velocity; j To represent the first j One hydrodynamic derivative; To adjust the first j When the hydrodynamic derivative is 1, the first k Group lateral velocity; For the first time without adjusting the hydrodynamic derivative k Group lateral velocity; To adjust the first j When the hydrodynamic derivative is 1, the first k Group turning speed; For the first time without adjusting the hydrodynamic derivative k Group turning speed.

[0010] More preferably, the simplified mechanism model of ship maneuvering motion = ship maneuvering motion model - non-critical hydrodynamic derivative terms.

[0011] More preferably, the simplified mechanism modeling method for ship maneuvering motion further includes the following steps: The amplitude, frequency, and duration of the rudder angle input signal are optimized using Fisher's information matrix theory to generate motion state data containing nonlinear dynamic information, which serves as the training set. A simplified mechanism model of ship maneuvering motion was trained using a training set; Z-shaped test data at different rudder angles are input into a simplified mechanism model of ship maneuvering motion for ship motion prediction; the Z-shaped test data is motion state data.

[0012] Secondly, this application provides a simplified mechanism modeling system for ship maneuvering motions, comprising: The correlation analysis module is used to input motion state data under different rudder angles into the ship maneuvering motion model, calculate the correlation between different hydrodynamic derivatives in the longitudinal, lateral and turning directions, and merge hydrodynamic derivatives with correlation coefficients exceeding the preset coefficient into a group. The sensitivity analysis module is used to adjust the grouped hydrodynamic derivatives according to a certain ratio, obtain multiple numerical simulations of maneuvering motions, calculate the overall sensitivity value of the hydrodynamic derivatives relative to the ship's horizontal motion at different ratios, merge the hydrodynamic derivatives corresponding to the overall sensitivity value that is greater than the preset sensitivity value, and simplify the ship maneuvering motion model to form a simplified mechanism model of ship maneuvering motion.

[0013] More preferably, the correlation analysis module is used to calculate the correlation coefficient between different hydrodynamic derivatives using the Spearman correlation coefficient method, where the Spearman correlation coefficient is:

[0014] in, For the first hydrodynamic derivative corresponding to the first i Group motion state data; For the second hydrodynamic derivative corresponding to the first i Group motion state data; The mean of all motion state data corresponding to the first hydrodynamic derivative; This is the mean of all motion state data corresponding to the second hydrodynamic derivative.

[0015] More preferably, the overall sensitivity value of the hydrodynamic derivative relative to the ship's motion in the horizontal plane in the sensitivity analysis module is:

[0016] in, k The first numerical simulation representing the manipulation motion k Group data; N The total amount of data used in the numerical simulation of manipulating motion; For the first time without adjusting the hydrodynamic derivative k Group longitudinal velocity; To adjust the first j When the hydrodynamic derivative ratio is 1, the first k Group longitudinal velocity; j To represent the first j One hydrodynamic derivative; To adjust the first j When the hydrodynamic derivative is 1, the first k Group lateral velocity; For the first time without adjusting the hydrodynamic derivative k Group lateral velocity; To adjust the first j When the hydrodynamic derivative is 1, the first k Group turning speed; For the first time without adjusting the hydrodynamic derivative k Group turning speed.

[0017] More preferably, the simplified mechanism modeling system for ship maneuvering motion also includes: The optimal excitation module is used to optimize the amplitude, frequency, and duration of the rudder angle input signal using Fisher information matrix theory, and generate motion state data containing nonlinear dynamic information as a training set. The system identification module is used to identify the hydrodynamic derivatives in the simplified mechanism model of ship maneuvering motion using the training set; The motion prediction module is used to input Z-shaped test data at different rudder angles into a simplified mechanism model of ship maneuvering motion for ship motion prediction.

[0018] Thirdly, this application provides an electronic device, comprising: at least one memory for storing a program; and at least one processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to execute the method described in the first aspect or a further preferred embodiment of the first aspect.

[0019] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the method described in the first aspect or a further preferred embodiment of the first aspect.

[0020] Fifthly, this application provides a computer program product that, when run on a processor, causes the processor to perform the method described in the first aspect or a further preferred embodiment of the first aspect.

[0021] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0022] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art: This application provides a simplified mechanism modeling method for ship maneuvering motions. Through correlation and sensitivity analysis, the hydrodynamic derivatives in the ship maneuvering motion model are grouped and filtered. Combined with the optimal excitation method, a simplified mechanism model is constructed, effectively reducing the complexity of the ship maneuvering motion model and improving identification efficiency and accuracy. Under Z-shaped test data with different rudder angles and data scales, the simplified mechanism model demonstrates excellent predictive performance and generalization ability, especially under limited experimental conditions or insufficient data, exhibiting higher engineering application value. This application provides new theoretical directions and methodological support for the accurate modeling of ship maneuvering motions. Attached Figure Description

[0023] Figure 1 This is a flowchart of a simplified mechanism modeling method for ship maneuvering motion provided in this application; Figure 2 This is a heatmap of the correlation coefficient of hydrodynamic derivatives provided in the embodiments of this application; Figure 3 This is a schematic diagram of the local sensitivity analysis results of the hydrodynamic derivative provided in the embodiments of this application; Figure 4(a) shows the local and overall sensitivity values ​​obtained by adjusting the hydrodynamic derivative by a +10% ratio according to the embodiment of this application. Figure 4(b) shows the local and overall sensitivity values ​​obtained by adjusting the hydrodynamic derivative by a ratio of -10% according to the embodiment of this application. Figure 4(c) shows the local and overall sensitivity values ​​obtained by adjusting the hydrodynamic derivative by a +30% ratio according to the embodiment of this application. Figure 4(d) shows the local and overall sensitivity values ​​obtained by adjusting the hydrodynamic derivative by a ratio of -30% according to the embodiment of this application. Figure 4(e) shows the local and overall sensitivity values ​​obtained by adjusting the hydrodynamic derivative by a +50% ratio according to the embodiment of this application. Figure 4(f) shows the local and overall sensitivity values ​​obtained by adjusting the hydrodynamic derivative by a ratio of -50% according to the embodiment of this application. Figure 5 This is the time series of the optimized rudder angle input signal provided in the embodiments of this application; Figure 6 This is a schematic diagram of the average absolute value of the overall sensitivity of the hydrodynamic derivative provided in the embodiments of this application; Figure 7(a) is an example of an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 7(b) shows the embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 7(c) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 7(d) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 7(e) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 7(f) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 8(a) is an example of an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 8(b) shows the embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 8(c) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 8(d) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 8(e) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 8(f) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 9(a) is an example of an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 9(b) is an example of an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 9(c) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering motion prediction results; Figure 9(d) is an embodiment provided in this application. Z-shaped test Schematic diagram of ship maneuvering prediction results. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0025] In this application, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A existing alone, A and B existing simultaneously, and B existing alone. In this application, the symbol " / " indicates that the related objects are in an "or" relationship, for example, A / B means A or B.

[0026] The terms "first" and "second," etc., used in the specification and claims of this application are used to distinguish different objects, rather than to describe a specific order of objects.

[0027] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0028] In the description of the embodiments in this application, unless otherwise stated, "multiple" means two or more.

[0029] The embodiments of this application are described below with reference to the accompanying drawings.

[0030] Firstly, such as Figure 1 As shown, this application provides a simplified mechanism modeling method for ship maneuvering motions, which specifically includes the following steps: Step S1: Correlation Analysis Correlation analysis was performed on the hydrodynamic derivatives in the ship maneuvering motion model to reveal the linear correlation between them, and the hydrodynamic derivatives with strong correlations were grouped. Specifically, the Spearman correlation coefficient method was used to calculate the correlation coefficients between different hydrodynamic derivatives in the longitudinal, lateral, and turning directions, and the hydrodynamic derivatives were grouped according to the magnitude of the correlation coefficients. Figure 2 As shown, the formula for calculating the Spearman correlation coefficient is:

[0031] in, For the first hydrodynamic derivative corresponding to the first i Group motion state data; For the second hydrodynamic derivative corresponding to the first i Group motion state data; The mean of all motion state data corresponding to the first hydrodynamic derivative; The mean of all motion state data corresponding to the second hydrodynamic derivative; In the simplified mechanism modeling of ship maneuvering motion, the results of correlation analysis serve as the basis for grouping hydrodynamic derivatives. Highly correlated hydrodynamic derivatives have similar effects on the output, so they can be considered as a group to further simplify the model structure. Through correlation analysis, not only can the linear correlation between hydrodynamic derivatives be clarified, but a solid theoretical foundation can also be laid for the final simplified mechanism modeling. Step S2: Sensitivity Analysis Sensitivity analysis was performed on the grouped hydrodynamic derivatives to assess the impact of each hydrodynamic derivative on the output of the ship maneuvering motion model, and to identify key hydrodynamic derivatives that significantly affect ship maneuvering motion. Specifically, an indirect method was used for sensitivity analysis. The value of a certain hydrodynamic derivative was adjusted by a certain proportion, and multiple numerical simulations of maneuvering motion were conducted. The changes in the motion state variables in the numerical simulation results were used as the basis for calculating the sensitivity of the hydrodynamic derivatives. Figure 3 As shown in Figures 4(a) to 4(f), the sensitivity calculation formula is: The local sensitivity value of a certain hydrodynamic derivative in the longitudinal dynamic equation with respect to longitudinal motion:

[0032] in, k The first numerical simulation representing the manipulation motion k Group data; N The total amount of data used in the numerical simulation of manipulating motion; For the first time without adjusting the hydrodynamic derivative k Group longitudinal velocity; To adjust the first jWhen the hydrodynamic derivative ratio is 1, the first k Group longitudinal velocity; j Representing the j One hydrodynamic derivative; The overall sensitivity of the hydrodynamic derivative to the ship's motion in the horizontal plane:

[0033] in, k The first numerical simulation representing the manipulation motion k Group data; N The total amount of data used in the numerical simulation of manipulating motion; For the first time without adjusting the hydrodynamic derivative k Group longitudinal velocity; To adjust the first j When the hydrodynamic derivative ratio is 1, the first k Group longitudinal velocity; j To represent the first j One hydrodynamic derivative; To adjust the first j When the hydrodynamic derivative is 1, the first k Group lateral velocity; For the first time without adjusting the hydrodynamic derivative k Group lateral velocity; To adjust the first j When the hydrodynamic derivative is 1, the first k Group turning speed; For the first time without adjusting the hydrodynamic derivative k Group turning speed; Sensitivity analysis can quantify the contribution of each hydrodynamic derivative to the model output, providing a basis for model simplification. Hydrodynamic derivatives with higher sensitivity are considered key parameters, while derivatives with lower sensitivity can be discarded or merged, thereby achieving simplified mechanism modeling. Based on the results of correlation analysis and sensitivity coupling analysis, a simplified mechanism model is constructed, retaining key hydrodynamic derivatives with low correlation but significant impact on ship motion. The simplified mechanism model takes the following form: Simplified Mechanism Model = Ship Maneuvering Motion Model - Non-critical Hydrodynamic Derivatives The simplified mechanism model simplifies the structure of the ship maneuvering motion model by scientifically grouping and screening hydrodynamic derivatives, reducing the model complexity, while retaining the key hydrodynamic derivatives that have a significant impact on ship maneuvering motion, thus improving the identification efficiency and accuracy of the ship maneuvering motion model. The original model is a ship maneuvering motion model; Step S3: Optimal incentive design Based on Fisher's information matrix theory, optimal excitation design is performed. By optimizing the amplitude, frequency, and duration of the rudder angle input signal, a high-quality training dataset containing rich nonlinear dynamic information is generated. Specifically, a mathematical model of the optimal excitation design problem is constructed, and the optimization objective is defined as minimizing the trace of the inverse Fisher's information matrix.

[0034] in, To find the rank function; An optimization algorithm is used to optimize the parameters of the rudder angle input signal. The optimized rudder angle signal is as follows: Figure 5 As shown, its time series has a higher information content, which can significantly stimulate the nonlinear dynamic characteristics of ship maneuvering motion, reduce parameter drift, and improve identification accuracy and model stability.

[0035] Step S4: System Identification and Motion Prediction Using standard Z-shaped test data of different rudder angles and scales, as well as high-quality training data generated by optimal excitation design, the simplified mechanism model was trained and validated to evaluate its ship motion prediction accuracy and applicability under different test conditions. The validation results show that the simplified mechanism model exhibits excellent generalization performance and ship motion prediction accuracy under small-scale, small-rudder-angle data conditions, especially when training data is insufficient or linear characteristics dominate, its performance is better than the original mechanism model. When training data is sufficient and includes nonlinear dynamic characteristics under different amplitude maneuvers, the performance difference between the simplified mechanism model and the original mechanism model is not significant, but it still has high prediction accuracy.

[0036] Secondly, this application provides a simplified mechanism modeling system for ship maneuvering motions, comprising: The correlation analysis module is used to input motion state data under different rudder angles into the ship maneuvering motion model, calculate the correlation between different hydrodynamic derivatives in the longitudinal, lateral and turning directions, and merge hydrodynamic derivatives with correlation coefficients exceeding the preset coefficient into a group. The sensitivity analysis module is used to adjust the grouped hydrodynamic derivatives according to a certain ratio, obtain multiple numerical simulations of maneuvering motions, calculate the overall sensitivity value of the hydrodynamic derivatives relative to the ship's horizontal motion at different ratios, merge the hydrodynamic derivatives corresponding to the overall sensitivity value that is greater than the preset sensitivity value, and simplify the ship maneuvering motion model to form a simplified mechanism model of ship maneuvering motion.

[0037] More preferably, the correlation analysis module is used to calculate the correlation coefficient between different hydrodynamic derivatives using the Spearman correlation coefficient method, where the Spearman correlation coefficient is:

[0038] in, For the first hydrodynamic derivative corresponding to the first i Group motion state data; For the second hydrodynamic derivative corresponding to the first i Group motion state data; The mean of all motion state data corresponding to the first hydrodynamic derivative; This is the mean of all motion state data corresponding to the second hydrodynamic derivative.

[0039] More preferably, the overall sensitivity value of the hydrodynamic derivative relative to the ship's motion in the horizontal plane in the sensitivity analysis module is:

[0040] in, k The first numerical simulation representing the manipulation motion k Group data; N The total amount of data used in the numerical simulation of manipulating motion; For the first time without adjusting the hydrodynamic derivative k Group longitudinal velocity; To adjust the first j When the hydrodynamic derivative ratio is 1, the first k Group longitudinal velocity; j To represent the first j One hydrodynamic derivative; To adjust the first j When the hydrodynamic derivative is 1, the first k Group lateral velocity; For the first time without adjusting the hydrodynamic derivative k Group lateral velocity; To adjust the first j When the hydrodynamic derivative is 1, the first k Group turning speed; For the first time without adjusting the hydrodynamic derivative k Group turning speed.

[0041] More preferably, the simplified mechanism modeling system for ship maneuvering motion also includes: The optimal excitation module is used to optimize the amplitude, frequency, and duration of the rudder angle input signal using Fisher information matrix theory, and generate motion state data containing nonlinear dynamic information as a training set. The system identification module is used to identify the hydrodynamic derivatives in the simplified mechanism model of ship maneuvering motion using the training set; The motion prediction module is used to input Z-shaped test data at different rudder angles into a simplified mechanism model of ship maneuvering motion for ship motion prediction.

[0042] Example 1 Example 1 of this application focuses on identification modeling under small rudder angle Z-shaped test data: In this embodiment, using The Z-shaped test data is used to identify and model the original mechanistic model and the simplified mechanistic model. The identification and modeling results are then used to predict ship maneuvering motions for Z-shaped tests at different rudder angles. The specific steps include: collect Z-shaped test data includes: motion data such as the ship's longitudinal speed, lateral speed, and bow turning angular velocity; The collected data is input into the correlation analysis module to calculate the correlation coefficients between hydrodynamic derivatives and generate a correlation coefficient heatmap, such as... Figure 2 As shown, by analyzing the correlation coefficient heatmap, a strong linear correlation was found among some hydrodynamic derivatives; Hydrodynamic derivatives with strong correlations were grouped and input into the sensitivity analysis module. The values ​​of each hydrodynamic derivative were adjusted by percentages of +10%, -10%, +30%, -30%, +50%, and -50%, respectively. Multiple numerical simulations of maneuvering motions were performed to obtain local and overall sensitivity values ​​under different percentage changes. Figure 3 As shown in Figures 4(a) to 4(f); Based on the magnitude of the sensitivity values, key hydrodynamic derivatives that significantly affect ship maneuvering motion are selected, and a simplified mechanistic model is constructed, such as... Figure 6 As shown; Using the constructed simplified mechanism model, different rudder angles ( , , , , Z-shaped tests are used to predict ship maneuvering motions; The prediction results of the simplified mechanism model were compared and analyzed with those of the original mechanism model, as shown in Figures 7(a) to 7(f). The results show that the prediction accuracy of the simplified mechanism model is higher than that of the original mechanism model in different rudder angle control tests. Especially under large rudder angle conditions, the prediction results of the original mechanism model diverge, while the simplified mechanism model still has high prediction accuracy.

[0043] Example 2 Example 2 of this application focuses on identification modeling under large rudder angle Z-shaped test data: In this embodiment 2, using The Z-shaped test data is used to identify and model the original mechanistic model and the simplified mechanistic model. The identification and modeling results are then used to predict ship maneuvering motions for Z-shaped tests at different rudder angles. The specific steps include: collect Z-shaped test data includes motion data such as the ship's longitudinal speed, lateral speed, and bow turning angular velocity; The collected data is input into the correlation analysis module to calculate the correlation coefficients between hydrodynamic derivatives and generate a correlation coefficient heatmap, such as... Figure 2 As shown; by analyzing the correlation coefficient heatmap, it was found that there is a strong linear correlation among some hydrodynamic derivatives; Hydrodynamic derivatives with strong correlations were grouped and input into the sensitivity analysis module. The values ​​of each hydrodynamic derivative were adjusted by percentages of +10%, -10%, +30%, -30%, +50%, and -50%, respectively. Multiple numerical simulations of maneuvering motions were performed to obtain local and overall sensitivity values ​​under different percentage changes. Figure 3 As shown in Figure 4; Based on the magnitude of the sensitivity values, key hydrodynamic derivatives that significantly affect ship maneuvering motion are selected, and a simplified mechanistic model is constructed, such as... Figure 6 As shown; Using the constructed simplified mechanism model, different rudder angles ( , , , , Z-shaped tests are used to predict ship maneuvering motions; The prediction results of the simplified mechanism model were compared and analyzed with those of the original mechanism model, as shown in Figures 8(a) to 8(f). The results show that as the Z-shaped test angle decreases, the prediction accuracy of the ship's position and three-axis velocity gradually decreases. However, the overall prediction accuracy of the simplified mechanism model is higher than that of the original mechanism model, and there is no divergence in motion prediction.

[0044] Example 3 Example 3 of this application focuses on identification and modeling under multiple sets of Z-shaped test data with different rudder angles: In this embodiment 3, multiple sets of Z-shaped test data with different rudder angles (including) were used. , , as well as , , , , The original mechanism model and the simplified mechanism model are identified and modeled, and the identification and modeling results are used to... The Z-shaped test for predicting ship maneuvering motions includes the following steps: Collect multiple sets of Z-shaped test data with different rudder angles, including motion state data such as the ship's longitudinal speed, lateral speed, and bow turning angular velocity; The collected data is input into the correlation analysis module to calculate the correlation coefficients between hydrodynamic derivatives and generate a correlation coefficient heatmap, such as... Figure 2 As shown; by analyzing the correlation coefficient heatmap, it was found that there is a strong linear correlation among some hydrodynamic derivatives; Hydrodynamic derivatives with strong correlations were grouped and input into the sensitivity analysis module. The values ​​of each hydrodynamic derivative were adjusted by percentages of +10%, -10%, +30%, -30%, +50%, and -50%, respectively. Multiple numerical simulations of maneuvering motions were performed to obtain local and overall sensitivity values ​​under different percentage changes. Figure 3 As shown in Figure 4; Based on the magnitude of the sensitivity values, key hydrodynamic derivatives that significantly affect ship maneuvering motion are selected, and a simplified mechanistic model is constructed, such as... Figure 6 As shown; Using the constructed simplified mechanism model to Z-shaped tests are used to predict ship maneuvering motions; The prediction results of the simplified mechanism model were compared and analyzed with those of the original mechanism surface model, as shown in Figures 9(a) to 9(d). The results show that when trained with small rudder angle Z-shaped test data, the simplified mechanism model has a significantly higher accuracy in predicting ship maneuvering motion than the original mechanism model; when trained with large rudder angle Z-shaped test data, the simplified mechanism model has a slightly higher prediction accuracy than the original mechanism model; when trained with multiple sets of Z-shaped test data, the simplified mechanism model has a higher prediction accuracy for ship position than the original mechanism model, while its prediction accuracy for ship three-axis velocities is comparable to that of the original mechanism model.

[0045] In summary, this application scientifically groups and filters the hydrodynamic derivatives in the ship maneuvering motion model through correlation and sensitivity analysis. Combined with optimal excitation design methods, a simplified mechanistic model is constructed, effectively reducing model complexity and improving identification efficiency and accuracy. Under Z-shaped test data with different rudder angles and data scales, the simplified mechanistic model demonstrates excellent predictive performance and generalization ability, especially under limited experimental conditions or insufficient data, exhibiting higher engineering application value. This application provides new theoretical directions and methodological support for the accurate modeling of ship maneuvering motions.

[0046] It is understood that the detailed functional implementation of each of the above modules can be found in the description of the aforementioned method embodiments, and will not be repeated here.

[0047] It should be understood that the above-described device is used to execute the methods in the above embodiments. The implementation principle and technical effect of the corresponding program modules in the device are similar to those described in the above methods. The working process of the device can be referred to the corresponding process in the above methods, and will not be repeated here.

[0048] Based on the methods in the above embodiments, this application provides an electronic device that may include a processor, a communications interface, a memory, and a communication bus, wherein the processor, communications interface, and memory communicate with each other via the communication bus. The processor may invoke logical instructions stored in the memory to execute the methods in the above embodiments.

[0049] Furthermore, the logical instructions in the aforementioned memory 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 this application, in essence, or the part that contributes to the prior art, or a portion 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 this application.

[0050] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0051] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0052] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0053] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0054] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0055] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A simplified mechanism modeling method for ship maneuvering motion, characterized in that, The hydrodynamic derivative is simplified through a dual coupling analysis of correlation and sensitivity, specifically including the following steps: The motion state data under different rudder angles are input into the ship maneuvering motion model. The correlation between different hydrodynamic derivatives in the longitudinal, lateral and bow-turning directions is calculated respectively. Hydrodynamic derivatives with correlation coefficients exceeding the preset coefficient are merged into a group. The hydrodynamic derivatives after grouping are adjusted according to a certain ratio. Numerical simulations of multiple maneuvering motions are obtained. The overall sensitivity value of the hydrodynamic derivatives relative to the ship's motion in the horizontal plane is calculated at different ratios. Hydrodynamic derivatives with an overall sensitivity value greater than the preset sensitivity value are merged to simplify the ship maneuvering motion model and form a simplified mechanism model of ship maneuvering motion.

2. The simplified mechanism modeling method for ship maneuvering motion according to claim 1, characterized in that, The correlation coefficient between different hydrodynamic derivatives was calculated using the Spearman correlation coefficient method. The Spearman correlation coefficient is: in, For the first hydrodynamic derivative corresponding to the first i Group motion state data; For the second hydrodynamic derivative corresponding to the first i Group motion state data; The mean of all motion state data corresponding to the first hydrodynamic derivative; This is the mean of all motion state data corresponding to the second hydrodynamic derivative.

3. The simplified mechanism modeling method for ship maneuvering motion according to claim 1, characterized in that, The overall sensitivity of the hydrodynamic derivative to the ship's motion in the horizontal plane is: in, k The first numerical simulation representing the manipulation motion k Group data; N The total amount of data used in the numerical simulation of manipulating motion; For the first time without adjusting the hydrodynamic derivative k Group longitudinal velocity; To adjust the first j When the hydrodynamic derivative ratio is 1, the first k Group longitudinal velocity; j To represent the first j One hydrodynamic derivative; To adjust the first j When the hydrodynamic derivative is 1, the first k Group lateral velocity; For the first time without adjusting the hydrodynamic derivative k Group lateral velocity; To adjust the first j When the hydrodynamic derivative is 1, the first k Group turning speed; For the first time without adjusting the hydrodynamic derivative k Group turning speed.

4. The simplified mechanism modeling method for ship maneuvering motion according to any one of claims 1 to 3, characterized in that, It also includes the following steps: The amplitude, frequency, and duration of the rudder angle input signal are optimized using Fisher information matrix theory to generate motion state data containing nonlinear dynamic information, which serves as a training set. The hydrodynamic derivatives in the simplified mechanism model of ship maneuvering motion are identified using the training set; Z-shaped test data at different rudder angles are input into a simplified mechanism model of ship maneuvering motion for ship motion prediction.

5. A simplified mechanism modeling system for ship maneuvering motions, characterized in that, include: The correlation analysis module is used to input motion state data under different rudder angles into the ship maneuvering motion model, calculate the correlation between different hydrodynamic derivatives in the longitudinal, lateral and turning directions, and merge hydrodynamic derivatives with correlation coefficients exceeding the preset coefficient into a group. The sensitivity analysis module is used to adjust the grouped hydrodynamic derivatives according to a certain ratio, obtain multiple numerical simulations of maneuvering motions, calculate the overall sensitivity value of the hydrodynamic derivatives relative to the ship's horizontal motion at different ratios, merge the hydrodynamic derivatives corresponding to the overall sensitivity value that is greater than the preset sensitivity value, and simplify the ship maneuvering motion model to form a simplified mechanism model of ship maneuvering motion.

6. The simplified mechanism modeling system for ship maneuvering motion according to claim 5, characterized in that, The correlation analysis module is used to calculate the correlation coefficient between different hydrodynamic derivatives using the Spearman correlation coefficient method. The Spearman correlation coefficient is: in, For the first hydrodynamic derivative corresponding to the first i Group motion state data; For the second hydrodynamic derivative corresponding to the first i Group motion state data; The mean of all motion state data corresponding to the first hydrodynamic derivative; This is the mean of all motion state data corresponding to the second hydrodynamic derivative.

7. The simplified mechanism modeling system for ship maneuvering motion according to claim 6, characterized in that, The overall sensitivity value of the hydrodynamic derivative relative to the ship's motion in the horizontal plane in the sensitivity analysis module is: in, k The first numerical simulation representing the manipulation motion k Group data; N The total amount of data used in the numerical simulation of manipulating motion; For the first time without adjusting the hydrodynamic derivative k Group longitudinal velocity; To adjust the first j When the hydrodynamic derivative ratio is 1, the first k Group longitudinal velocity; j To represent the first j One hydrodynamic derivative; To adjust the first j When the hydrodynamic derivative is 1, the first k Group lateral velocity; For the first time without adjusting the hydrodynamic derivative k Group lateral velocity; To adjust the first j When the hydrodynamic derivative is 1, the first k Group turning speed; For the first time without adjusting the hydrodynamic derivative k Group turning speed.

8. The simplified mechanism modeling system for ship maneuvering motion according to any one of claims 5 to 7, characterized in that, Also includes: The optimal excitation module is used to optimize the amplitude, frequency, and duration of the rudder angle input signal by using Fisher's information matrix theory to generate motion state data containing nonlinear dynamic information as a training set. The system identification module is used to identify the hydrodynamic derivatives in the simplified mechanism model of ship maneuvering motion using the training set; The motion prediction module is used to input Z-shaped test data at different rudder angles into a simplified mechanism model of ship maneuvering motion for ship motion prediction.

9. An electronic device, characterized in that, include: At least one memory for storing computer programs; At least one processor is configured to execute a program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to perform the method as described in any one of claims 1-4.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is run on the processor, it causes the processor to perform the method as described in any one of claims 1-4.

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