Submersible dynamical model modeling method and device, electronic equipment and storage medium

Abstract

The invention provides a submersible dynamical model modeling method and device, electronic equipment and a storage medium, and belongs to the technical field of submersible, and the method comprises the steps: building an initial model of a submersible dynamical model; respectively determining the influence significance of each hydrodynamic coefficient in the initial model on the output; gradually removing a target coefficient item which affects the minimum significance in the initial model, and determining the goodness of fit of the initial model after removing one target coefficient item each time; the target coefficient is a hydrodynamic coefficient of which the influence significance is lower than a first threshold value; if the goodness of fit is lower than a second threshold value after the target coefficient item is removed this time, the target coefficient item removed this time is reserved in the initial model, and the current initial model serves as a dynamic model. The dynamical model can be simplified as much as possible while the precision of the dynamical model is ensured, so that the calculation efficiency of the dynamical model is improved, and both the model precision and the calculation efficiency are considered.

Description

Technical Field

[0001] This invention relates to the field of submersible technology, and in particular to a method, apparatus, electronic device, and storage medium for modeling submersible dynamics. Background Technology

[0002] The dynamic model of a submersible can predict the forces and moments acting on it based on variables such as velocity and angular velocity. Existing submersible dynamic models either retain too many hydrodynamic coefficients, leading to low computational efficiency, or remove too many hydrodynamic coefficients, resulting in low accuracy. Therefore, it is necessary to establish a submersible dynamic model that balances computational efficiency and accuracy. Summary of the Invention

[0003] This invention provides a method, apparatus, electronic device, and storage medium for modeling submersible dynamics, in order to solve the technical problem that existing submersible dynamics models cannot simultaneously achieve both computational efficiency and accuracy.

[0004] This invention provides a method for modeling the dynamics of a submersible, comprising: An initial model for establishing the dynamics of the submersible; Determine the significance of the impact of each hydrodynamic coefficient in the initial model on the output; The target coefficient terms with the least significant impact are successively removed from the initial model, and the goodness of fit of the initial model is determined after each removal of a target coefficient term; the target coefficient is the hydrodynamic coefficient with a significant impact lower than a first threshold. If the goodness of fit is lower than the second threshold after removing the target coefficient term, then the target coefficient term removed in this instance is retained in the initial model, and the current initial model is used as the dynamic model.

[0005] According to the submersible dynamics modeling method provided by the present invention, the initial model for establishing the submersible dynamics model includes: Acquire multiple motion state samples of the submersible; Based on each of the motion state samples, the space restraint motion simulation of the submersible is performed to obtain the force and torque samples corresponding to each of the motion state samples. The initial model is obtained by fitting each of the motion state samples and each of the force and torque samples.

[0006] According to a submersible dynamics modeling method provided by the present invention, the step of obtaining multiple motion state samples of the submersible includes: Multiple motion state samples were obtained through Latin hypercube sampling.

[0007] According to the submersible dynamics modeling method provided by the present invention, the step of determining the significance of the influence of each hydrodynamic coefficient in the initial model on the output includes: The significance of the effect was determined by hypothesis testing with the null hypothesis that the hydrodynamic coefficient is equal to zero and the alternative hypothesis that the hydrodynamic coefficient is not equal to zero.

[0008] According to a submersible dynamics modeling method provided by the present invention, determining the goodness of fit of the initial model includes: Each motion state sample of the submersible is input into the initial model to obtain the predicted force and torque values ​​corresponding to each motion state sample output by the initial model. The goodness of fit is determined based on the various force and torque samples of the submersible and the various predicted values ​​of the force and torque.

[0009] According to a submersible dynamics modeling method provided by the present invention, the step of determining the goodness of fit based on the various force and torque samples and the various predicted force and torque values ​​of the submersible includes: Calculate the average value of each of the force and torque samples; Calculate the first difference between each of the force and torque samples and the average value, and the first sum of squares of each of the first differences; Calculate the second difference between each of the force and torque samples and the corresponding predicted force and torque values, and the second sum of squares of each of the second differences; The goodness of fit is calculated based on the first sum of squares and the second sum of squares.

[0010] The present invention also provides a submersible dynamics modeling device, comprising: The modeling module is used to create an initial model for the submersible's dynamics. The determination module is used to determine the significance of the influence of each hydrodynamic coefficient in the initial model on the output; A simplification module is used to successively remove the target coefficient terms with the least significant impact from the initial model, and to determine the goodness of fit of the initial model after removing one target coefficient term at a time; the target coefficient is the hydrodynamic coefficient with a significant impact lower than a first threshold. The processing module is configured to retain the removed target coefficient term in the initial model and use the current initial model as the dynamic model if the goodness of fit is lower than the second threshold after removing the target coefficient term.

[0011] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the submersible dynamics modeling method described above.

[0012] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the submersible dynamics modeling method as described above.

[0013] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the submersible dynamics modeling method as described above.

[0014] The submersible dynamics modeling method, device, electronic equipment, and storage medium provided by this invention determine the significance of the influence of each hydrodynamic coefficient on the output in the initial model, successively remove the hydrodynamic coefficient terms that have the least impact on the output of the initial model, and stop removing hydrodynamic coefficient terms when the goodness of fit of the initial model is lower than a second threshold. This can simplify the dynamics model as much as possible while ensuring the accuracy of the dynamics model, thereby improving the computational efficiency of the dynamics model and balancing model accuracy and computational efficiency. Attached Figure Description

[0015] 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.

[0016] Figure 1 This is a flowchart illustrating the submersible dynamics modeling method provided by the present invention.

[0017] Figure 2 This is a schematic diagram of the sampling results of the Latin hypercube experiment provided by the present invention.

[0018] Figure 3 This is one of the schematic diagrams illustrating the correlation between hydrodynamic coefficients and forces and moments provided by this invention.

[0019] Figure 4 This is the second schematic diagram illustrating the correlation between the hydrodynamic coefficients and the forces and moments provided by this invention.

[0020] Figure 5 This is a schematic diagram of the goodness of fit provided by the present invention.

[0021] Figure 6This is a schematic diagram of the submersible dynamics modeling device provided by the present invention.

[0022] Figure 7 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0023] 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 with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0024] The following is combined Figures 1-7 This invention describes the submersible dynamics modeling method, apparatus, electronic equipment, and storage medium provided by the present invention.

[0025] Figure 1 This is a flowchart illustrating the submersible dynamics modeling method provided by the present invention, as shown below. Figure 1 As shown, steps S1, S2 and S3 are included but are not limited to.

[0026] Step S1: Establish the initial model of the submersible dynamics model.

[0027] The input to the submersible's dynamic model is its motion state, which mainly includes velocity and angular velocity. Velocity and angular velocity include longitudinal velocity, lateral velocity, vertical velocity, roll angular velocity, pitch angular velocity, and turning angular velocity. The output of the dynamic model is the forces and moments acting on the submersible, including longitudinal force, lateral force, vertical force, roll moment, pitch moment, and turning moment. Each input term has hydrodynamic coefficients. The motion state determines the forces and moments acting on the submersible.

[0028] In one embodiment, step S1 may specifically include: Acquire multiple motion state samples of the submersible; Based on each of the motion state samples, the space restraint motion simulation of the submersible is performed to obtain the force and torque samples corresponding to each of the motion state samples. The initial model is obtained by fitting each of the motion state samples and each of the force and torque samples.

[0029] This allows for the establishment of an initial model by fitting the input and output samples.

[0030] In one embodiment, acquiring multiple motion state samples of the submersible may specifically include: Multiple motion state samples were obtained through Latin hypercube sampling.

[0031] Multiple motion state samples can be obtained from a large number of samples through the Latin hypercube experiment, ensuring that the motion state samples are evenly distributed. Figure 2 The results are from a Latin hypercube experiment, where u, v, w, p, q, and r represent longitudinal velocity, lateral velocity, vertical velocity, roll angular velocity, pitch angular velocity, and bow angular velocity, respectively. As can be seen, the motion state samples cover each motion interval, without any excessive data clustering.

[0032] For simulating submersible motion, existing technologies do not consider the mutual interference between the rudder, propeller, and hull. Hydrodynamic coefficient identification often involves decoupling analysis, but the mutual interference between the rudder, propeller, and hull is difficult to ignore, and decoupling analysis methods easily lead to reduced model accuracy. To improve model accuracy, this invention employs spatially constrained motion simulation. The content of spatially constrained motion simulation includes: Under low-speed conditions, the longitudinal velocity of the large submersible varies from 0.1 m / s to 0.4 m / s, while the lateral and vertical velocities vary from ±0.8 m / s and ±0.6 m / s, respectively. The maximum values ​​of the roll angular velocity, pitch angular velocity, and bow angular velocity do not exceed 10 deg / s. Under low-speed motion conditions, the integrated simulation considers the motion of the submersible's tail rudder, bow rudder, tail propeller, and main hull. There are a total of 6 outer domains, namely bow rudder domain 1, tail rudder domains 2 and 3, tail propeller domain 4, hull body domain 5, and flow field domain 6. The motion forms of each domain are shown in Table 1. The rotational angular velocity of the rudder is 2 deg / s, and the propeller speed is 80 rpm. In the CFD (Computational Fluid Dynamics) software, the motion of the submersible is executed according to the velocity and angular velocity samples to complete the spatial constraint motion simulation and obtain the force and torque samples.

[0033] Table 1 Computation Domain Settings

[0034] Then, 80% of the sample pairs can be used for fitting to obtain the initial model.

[0035] While submersible motion can generally be simulated by defining formulas for velocity and angular velocity, this method is prone to problems such as independent variable correlation or the velocity points not covering the entire calculation interval, leading to excessive data aggregation and making it difficult to guarantee model accuracy. This invention obtains multiple motion state samples through Latin hypercube experimental sampling and multiple force and torque samples through spatially constrained motion simulation, then performs fitting to ensure model accuracy.

[0036] The initial model obtained from the fitting will have hundreds of hydrodynamic coefficients, most of which are negligible and unimportant. Therefore, the initial model needs to be simplified to improve the computational efficiency of the model.

[0037] To demonstrate that most hydrodynamic coefficients can be neglected, this invention employs Pearson correlation analysis to calculate the correlation between each hydrodynamic coefficient term and the forces and moments in the initial model. The results are as follows: Figure 3 and Figure 4 As shown, the horizontal axis represents the sequence number of the hydrodynamic coefficient term, and the vertical axis represents the correlation; X, Z, M, Y, K, and N represent the longitudinal force, vertical force, pitching moment, lateral force, rolling moment, and turning moment, respectively. The correlation r ranges from [-1, 1]. This indicates that the hydrodynamic coefficient term is negatively correlated with the forces and moments applied. This indicates that the hydrodynamic coefficient is positively correlated with the forces and moments applied. This indicates that there is no correlation between the hydrodynamic coefficient and the forces and moments. The larger the absolute value of the correlation for a hydrodynamic coefficient, the greater its impact on the hull's motion performance. The classification of correlation r is shown in Table 2.

[0038] Table 2. Degree of association of Pearson correlation. ;

[0039] It can be seen that most of the hydrodynamic coefficient terms have extremely low correlation, so it is necessary to simplify the initial model.

[0040] Step S2: Determine the significance of the influence of each hydrodynamic coefficient in the initial model on the output.

[0041] The significance of the impact represents the degree of influence of hydrodynamic coefficients on forces and moments. Hydrodynamic coefficient terms with high significance should be retained, while those with low significance should be removed, thereby simplifying the model as much as possible without affecting its accuracy.

[0042] In one embodiment, step S2 may specifically include: The significance of the effect was determined by hypothesis testing with the null hypothesis that the hydrodynamic coefficient is equal to zero and the alternative hypothesis that the hydrodynamic coefficient is not equal to zero.

[0043] Hypothesis testing, also known as statistical hypothesis testing, is an important branch of mathematical statistics. The basic concept of hypothesis testing is to provide a positive or negative answer to an uncertain problem based on past information; it is a method of proof by contradiction with probabilistic properties. That is, given an alternative hypothesis... Given this premise, when making judgments about the constructed rules, one chooses to accept or reject the null hypothesis. If you refuse If so, then the alternative hypothesis is accepted. .

[0044] Null hypothesis It can be Alternative hypothesis It can be , Let be the i-th hydrodynamic coefficient in the i-th equation of the initial model. If the null hypothesis is true, it means that the effect of this hydrodynamic coefficient is insignificant and its role in the equation can be ignored, so the hydrodynamic coefficient term can be deleted from the equation; if the null hypothesis is false, it means that the hydrodynamic coefficient term in the equation has a significant effect on the forces and moments on the hull.

[0045] The ratio of the hydrodynamic coefficient to its standard error can be calculated to obtain the t-value. Then, the t-distribution table can be consulted or software can be used to calculate the P-value. The P-value is the probability that |T| ≥ |t|, where T is a random variable following a t-distribution. The larger the P-value, the smaller the significance of the influence; the smaller the P-value, the larger the significance of the influence.

[0046] Step S3: Successively remove the target coefficient terms with the least significant impact from the initial model, and determine the goodness of fit of the initial model after removing one target coefficient term each time; the target coefficient is the hydrodynamic coefficient with a significant impact below the first threshold.

[0047] Minimizing the significance of an impact is equivalent to maximizing the P-value. The target coefficient is a hydrodynamic coefficient that has no significant effect on force and torque. A P-value higher than 0.05 can be set to be equivalent to an impact significance lower than the first threshold, and a P-value lower than 0.05 can be set to be equivalent to an impact significance higher than the first threshold. Step S3 is equivalent to successively removing the target coefficient terms in ascending order of impact significance.

[0048] The goodness of fit of the initial model represents the effectiveness of fitting the motion state samples, force and torque samples. The greater the goodness of fit, the better the fitting effect, and the higher the accuracy of the initial model.

[0049] In one embodiment, step S3, determining the goodness of fit of the initial model, may specifically include: Input the various motion state samples of the submersible into the initial model to obtain the predicted values ​​of force and torque corresponding to each motion state sample output by the initial model; The goodness of fit is determined based on the various force and torque samples and the predicted values ​​of each force and torque of the submersible.

[0050] The motion state samples, force and torque samples here represent the remaining 20% ​​of the samples obtained through the Latin hypercube experiment. Therefore, the goodness of fit can be determined using the samples and predicted values.

[0051] In one embodiment, determining the goodness of fit based on the various force and torque samples and the predicted values ​​of the various forces and torques of the submersible may specifically include: Calculate the average value of each force and moment sample; Calculate the first difference between each force and torque sample and the average value, and the first sum of squares of each first difference; Calculate the second difference between each force and moment sample and the corresponding predicted force and moment value, and the second sum of squares of each second difference; The goodness of fit is calculated based on the first and second sums of squares.

[0052] Goodness of fit The calculation formula is ; Where n is the number of force and torque samples, For the i-th force and torque sample, These are the predicted force and torque values ​​corresponding to the i-th motion state sample. This represents the average value of each force and torque sample. The value range of is [0, 1]. The closer the value is to 1, the better the initial model fits the data. The closer the value is to 0, the worse the initial model fits.

[0053] In this way, the goodness of fit can be calculated from the samples of force and torque and the predicted values.

[0054] Step S4: If the goodness of fit is lower than the second threshold after removing the target coefficient term, then the target coefficient term removed in this step is retained in the initial model, and the current initial model is used as the dynamic model.

[0055] The second threshold can be 0.9. If the goodness of fit is lower than 0.9 after removing the target coefficient term with the least significant impact, it means that removing the target coefficient term will significantly affect the accuracy of the initial model. Therefore, the target coefficient term should not be removed and should be retained, and the initial model simplification is completed.

[0056] The initial model of this invention includes six equations corresponding to the longitudinal force X, lateral force Y, vertical force Z, roll moment K, pitch moment M, and turning moment N, respectively. Figure 5To illustrate the change in goodness of fit of the initial model after successively removing target coefficient terms from each equation, the horizontal axis represents the index of the target coefficient term in the equation, and the vertical axis represents the goodness of fit. It can be seen that after removing the 7th term in equation X, the 13th term in equation Y, the 13th term in equation Z, the 10th term in equation K, the 13th term in equation M, and the 13th term in equation N, the goodness of fit of each equation drops rapidly, indicating that these target coefficient terms cannot be deleted. By removing hydrodynamic coefficients that have little impact on the goodness of fit of the initial model and have insignificant effects on forces and moments, the model can be simplified as much as possible while maintaining its accuracy.

[0057] Following the simplified process described above, the final dynamic model obtained by this invention includes: ; ; ; ; ; ; in, The density of water, l For the length of the submersible, For longitudinal acceleration, For lateral acceleration, For vertical acceleration, This is the roll acceleration. The acceleration is the pitch angle. Let X'uu be the bow angular acceleration, and X'uu be the longitudinal force coefficient caused by the square of the longitudinal velocity. X'vr is the longitudinal force coefficient caused by longitudinal acceleration, X'wq is the longitudinal force coefficient caused by the product of lateral velocity and bow angular velocity, Y'ṙ is the lateral force coefficient caused by bow angular acceleration, and Y' Y'r is the lateral force coefficient caused by lateral acceleration, Y'v is the lateral force coefficient caused by lateral turning angular velocity, and Z' is the lateral force coefficient caused by lateral velocity. Z'ẇ is the vertical force coefficient caused by the pitch acceleration, Z'q is the vertical force coefficient caused by the pitch velocity, Z'w is the vertical force coefficient caused by the vertical velocity, K'ṗ is the roll moment coefficient caused by the roll acceleration, and K'p is the roll moment coefficient caused by the roll velocity. K'v is the rolling moment coefficient caused by lateral acceleration, K'vw is the rolling moment coefficient caused by the product of lateral velocities, and M' is the rolling moment coefficient caused by the product of lateral and vertical velocities. M'ẇ is the pitch moment coefficient caused by pitch angular acceleration, M'q is the pitch moment coefficient caused by pitch angular velocity, M'w is the pitch moment coefficient caused by vertical velocity, N'ṙ is the bow moment coefficient caused by turning angular acceleration, N'r is the bow moment coefficient caused by turning angular velocity, N'v is the bow moment coefficient caused by lateral velocity, and N' The torque coefficient caused by lateral acceleration.

[0058] As can be seen from the above, the submersible dynamics modeling method of the present invention determines the significance of the influence of each hydrodynamic coefficient on the output in the initial model, successively removes the hydrodynamic coefficient terms that have the least influence on the output of the initial model, and stops removing hydrodynamic coefficient terms when the goodness of fit of the initial model is lower than the second threshold. This can simplify the dynamic model as much as possible while ensuring the accuracy of the dynamic model, thereby improving the computational efficiency of the dynamic model and taking into account both model accuracy and computational efficiency.

[0059] like Figure 6 As shown, the submersible dynamics modeling device provided by the present invention includes, but is not limited to: The modeling module is used to create an initial model for the submersible's dynamics. The determination module is used to determine the significance of the influence of each hydrodynamic coefficient in the initial model on the output; The simplification module is used to successively remove the target coefficient terms with the least significant impact from the initial model, and to determine the goodness of fit of the initial model after removing one target coefficient term at a time; the target coefficients are hydrodynamic coefficients with a significant impact below the first threshold. The processing module is used to retain the removed target coefficients in the initial model if the goodness of fit is lower than the second threshold after removing the target coefficients, and to use the current initial model as the dynamic model.

[0060] The modeling module can also be used for: Acquire multiple motion state samples of the submersible; Based on the samples of each motion state, the space restraint motion of the submersible is simulated to obtain the force and torque samples corresponding to each motion state sample. The initial model is obtained by fitting the samples of each motion state and each force and torque.

[0061] The modeling module can also be used for: Multiple motion state samples were obtained through Latin hypercube sampling.

[0062] The determination module can also be used for: The significance of the effect was determined by hypothesis testing with the null hypothesis that the hydrodynamic coefficient is equal to zero and the alternative hypothesis that the hydrodynamic coefficient is not equal to zero.

[0063] The simplified module can also be used for: Input the various motion state samples of the submersible into the initial model to obtain the predicted values ​​of force and torque corresponding to each motion state sample output by the initial model; The goodness of fit is determined based on the various force and torque samples and the predicted values ​​of each force and torque of the submersible.

[0064] The simplified module can also be used for: Calculate the average value of each force and moment sample; Calculate the first difference between each force and torque sample and the average value, and the first sum of squares of each first difference; Calculate the second difference between each force and moment sample and the corresponding predicted force and moment value, and the second sum of squares of each second difference; The goodness of fit is calculated based on the first and second sums of squares.

[0065] It should be noted that the submersible dynamics modeling device provided by the present invention can execute the submersible dynamics modeling method described in any of the above embodiments during specific operation, which will not be elaborated in this embodiment.

[0066] Figure 7 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 7 As shown, the electronic device may include a processor, a communication interface, memory, and a communication bus, wherein the processor, communication interface, and memory communicate with each other through the communication bus. The processor can call logical instructions in the memory to execute a submersible dynamics modeling method, which includes: establishing an initial model of the submersible dynamics model; determining the significance of the influence of each hydrodynamic coefficient in the initial model on the output; successively removing the target coefficient terms with the smallest influence from the initial model, and determining the goodness of fit of the initial model after removing one target coefficient term each time; the target coefficients are hydrodynamic coefficients with influence significance below a first threshold; if the goodness of fit is below a second threshold after removing the target coefficient terms, the removed target coefficient terms are retained in the initial model, and the current initial model is used as the dynamics model.

[0067] Furthermore, the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, and 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.

[0068] On the other hand, the present invention also provides a computer program product, the computer program product including a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer is able to execute the submersible dynamics model modeling method provided in the above embodiments, the method including: establishing an initial model of the submersible dynamics model; determining the significance of the influence of each hydrodynamic coefficient in the initial model on the output; successively removing the target coefficient terms with the smallest influence significance in the initial model, and determining the goodness of fit of the initial model after removing one target coefficient term each time; the target coefficient is a hydrodynamic coefficient with an influence significance lower than a first threshold; if the goodness of fit is lower than a second threshold after removing the target coefficient term this time, the target coefficient term removed this time is retained in the initial model, and the current initial model is used as the dynamics model.

[0069] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the submersible dynamics modeling method provided in the above embodiments. The method includes: establishing an initial model of the submersible dynamics model; determining the significance of the influence of each hydrodynamic coefficient in the initial model on the output; successively removing the target coefficient terms with the smallest influence in the initial model, and determining the goodness of fit of the initial model after removing one target coefficient term each time; the target coefficients are hydrodynamic coefficients with influence significance lower than a first threshold; if the goodness of fit is lower than a second threshold after removing the target coefficient terms, the removed target coefficient terms are retained in the initial model, and the current initial model is used as the dynamics model.

[0070] 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.

[0071] 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.

[0072] 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.

Claims

1. A method of modeling a dynamics model of a submersible, the method comprising: The method comprises the following steps: establishing an initial model of a submersible dynamics model; determining the significance of each hydrodynamic coefficient in the initial model on the output respectively; gradually removing a target coefficient term with the least significance in the initial model, and determining the goodness of fit of the initial model after removing each target coefficient term; if the goodness of fit is lower than a second threshold after removing the target coefficient term, retaining the target coefficient term in the initial model, and taking the current initial model as the dynamics model.

2. The method of claim 1, wherein, The step of establishing an initial model of a submersible dynamics model comprises the following steps: obtaining a plurality of motion state samples of the submersible; performing spatial constraint motion simulation of the submersible based on each motion state sample to obtain a force and torque sample corresponding to each motion state sample; fitting each motion state sample and each force and torque sample to obtain the initial model.

3. The method of claim 2, wherein, The step of obtaining a plurality of motion state samples of the submersible comprises the following steps: obtaining a plurality of motion state samples by Latin hypercube sampling.

4. The method of claim 1, wherein, The step of determining the significance of each hydrodynamic coefficient in the initial model on the output respectively comprises the following steps: determining the significance by hypothesis testing with a null hypothesis that the hydrodynamic coefficient is equal to zero and an alternative hypothesis that the hydrodynamic coefficient is not equal to zero.

5. The method of claim 1, wherein, The step of determining the goodness of fit of the initial model comprises the following steps: inputting each motion state sample of the submersible into the initial model to obtain a force and torque prediction value corresponding to each motion state sample output by the initial model; determining the goodness of fit according to each force and torque sample of the submersible and each force and torque prediction value.

6. The method of modeling dynamics of a submersible of claim 5, wherein, The step of determining the goodness of fit according to each force and torque sample of the submersible and each force and torque prediction value comprises the following steps: calculating the average value of each force and torque sample; calculating a first difference between each force and torque sample and the average value, and a first sum of squares of each first difference; calculating a second difference between each force and torque sample and the corresponding force and torque prediction value, and a second sum of squares of each second difference; calculating the goodness of fit according to the first sum of squares and the second sum of squares.

7. A submersible vehicle dynamics model modeling apparatus characterized by, The method comprises the following steps: a modeling module for establishing an initial model of a submersible dynamics model; a determining module for determining the significance of each hydrodynamic coefficient in the initial model on the output respectively; a simplifying module for gradually removing a target coefficient term with the least significance in the initial model, and determining the goodness of fit of the initial model after removing each target coefficient term; the target coefficient is the hydrodynamic coefficient with a significance lower than a first threshold; a processing module for retaining the target coefficient term in the initial model if the goodness of fit is lower than a second threshold after removing the target coefficient term, and taking the current initial model as the dynamics model.

8. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The computer program is executed by the processor to implement the modeling method of the submersible dynamics model according to any one of claims 1 to 6. 9.A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the modeling method of the submersible dynamics model according to any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the modeling method of the submersible dynamics model according to any one of claims 1 to 6.

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