Method, device and electronic equipment for determining ship positioning capability based on subset simulation

Abstract

The application relates to the technical field of ship power positioning, and provides a ship positioning capacity determination method and device based on subset simulation and electronic equipment. The method comprises the following steps: acquiring multiple environmental parameter combinations to which a ship is subjected; determining corresponding thrust distribution results of the ship under each environmental parameter combination; respectively performing power positioning state evaluation on each thrust distribution result to obtain evaluation results corresponding to the thrust distribution results; respectively taking each environmental parameter combination and the corresponding evaluation result as input of a preset target function to obtain target function values corresponding to each environmental parameter combination; based on the target function values, optimization is performed through a subset simulation optimization method to obtain limit environmental parameter combinations for keeping positioning of the ship, and limit positioning capacity of the ship is determined according to the limit environmental parameter combinations. The application can accurately search for the most severe limit environmental parameter combinations, and improves the accuracy of limit positioning capacity evaluation of the ship.

Description

Technical Field

[0001] This application relates to the field of ship dynamic positioning technology, and in particular to a method, apparatus and electronic equipment for determining ship positioning capability based on subset simulation. Background Technology

[0002] The dynamic positioning system is the core control system of marine engineering equipment such as wind turbine installation vessels, pipe-laying and cable-laying vessels, crane vessels, and offshore oil platforms. It is used to maintain the position and heading stability of the vessel during offshore operations.

[0003] Dynamic positioning capability analysis is a crucial step in the ship design phase. The industry typically uses the minimum combination of environmental parameters that a ship can withstand from all directions as the core evaluation indicator. Overestimating positioning capability will compress the ship's actual operating window and fail to guarantee stable positioning; underestimating positioning capability will result in redundant power configurations in the propulsion and electrical systems, increasing construction costs.

[0004] Existing calculation methods include two approaches: First, the simplified assumption of wind, waves, and current moving in the same direction reduces the computational load, but it cannot cover the actual working conditions where wind, waves, and currents move in opposite directions, making it difficult to accurately match the worst combination of environmental parameters. Second, the method of enumerating combinations of wind, waves, and currents moving in opposite directions and solving for the limiting wind speed one by one suffers from large computational load, long processing time, and low solution efficiency. Summary of the Invention

[0005] In view of this, this application provides a method, apparatus and electronic device for determining ship positioning capability based on subset simulation, which can solve the technical problems in the existing ship dynamic positioning capability assessment, such as the inability to match actual operating conditions by assuming that wind, waves and current are in the same direction, and the large amount of computation and low efficiency of enumeration method to traverse different environmental combinations.

[0006] This application provides a method, apparatus, and electronic device for determining ship positioning capabilities based on subset simulation. The following description covers various aspects of this application, and the embodiments and beneficial effects described below can be referenced interchangeably.

[0007] Firstly, this application provides a method for determining ship positioning capabilities based on subset simulation, including:

[0008] The combination of multiple environmental parameters experienced by the ship is obtained, wherein the combination of environmental parameters includes at least wind speed, the angle between wind direction and ship heading, the angle between current direction and ship heading, and the angle between wave direction and ship heading.

[0009] Determine the thrust allocation results for the ship under various combinations of environmental parameters. The thrust allocation results include executable thrust allocation schemes or no executable thrust allocation schemes.

[0010] The dynamic positioning status is evaluated for each thrust distribution result, and the evaluation result corresponding to each thrust distribution result is obtained. The evaluation result is used to indicate whether the ship can be positioned.

[0011] Each combination of environmental parameters and its corresponding evaluation results are used as input to a preset objective function to obtain the objective function value corresponding to each combination of environmental parameters. The objective function is used to characterize whether the ship has omnidirectional positioning capability under the current wind speed.

[0012] Based on the objective function value, the combination of extreme environmental parameters for maintaining the ship's positioning is obtained through subset simulation optimization. The ship's extreme positioning capability is then determined based on the combination of extreme environmental parameters.

[0013] According to the embodiments of this application, the above-mentioned technical solution of this application has at least the following beneficial effects: This invention introduces a subset simulation optimization method combined with iterative solution of the objective function to solve for the combination of extreme environmental parameters. It does not rely on the simplified assumption of wind, waves, and currents being in the same direction, and can comprehensively cover actual operating conditions where wind, waves, and currents are in different directions. It can accurately search for the most severe combination of extreme environmental parameters, improving the accuracy of ship extreme positioning capability assessment. At the same time, compared with the traditional enumeration traversal method, it effectively reduces the computational load and solution time, significantly improving the solution efficiency of positioning capability analysis.

[0014] In one possible implementation of the first aspect above, the combination of multiple environmental parameters experienced by the ship is obtained, including:

[0015] For each parameter in the combination of environmental parameters, random sampling is performed within its corresponding preset search interval to obtain sampled values ​​that satisfy the preset probability distribution model corresponding to the parameters.

[0016] By combining the sampled values ​​of each parameter, we obtain the environmental parameter combination.

[0017] According to the embodiments of this application, the above-mentioned technical solution of this application has at least the following beneficial effects: by randomly sampling and combining environmental parameters within a preset search interval of each environmental parameter according to the corresponding probability distribution model, the combination of environmental parameters can conform to the parameter distribution law of the real marine environment, and the generated samples are more representative of the working conditions. It does not rely on the simplified assumption of wind, waves and currents being in the same direction, and can cover complex working conditions with multiple combinations. It also avoids the redundant calculations caused by full enumeration and traversal. It constructs a diverse set of environmental working conditions sample sets with an efficient sampling method, providing a reliable sample basis for the limit solution of subsequent subset simulation, and improving the rationality and efficiency of the overall solution.

[0018] In one possible implementation of the first aspect above, optimization is performed based on the objective function value using a subset simulation optimization method to obtain the combination of extreme environmental parameters for maintaining ship positioning, including:

[0019] S51, Based on the objective function values, construct a first set of objective function values, and extract the minimum value from the first set of objective function values ​​as the first minimum value;

[0020] S52, according to the preset sampling ratio, select the smallest number of objective function values ​​corresponding to the sampling ratio from the first objective function value set to obtain the objective function value seed set;

[0021] S53, Select the maximum value from the seed set of objective function values ​​as the critical value;

[0022] S54, construct a second combination of environmental parameters based on the combination of environmental parameters corresponding to the objective function values ​​in the seed set of objective function values;

[0023] S55, calculate the objective function value corresponding to each combination of second environmental parameters to obtain the set of second objective function values;

[0024] S56, if the objective function value in the second objective function value set is not greater than the critical value, extract the minimum value from the second objective function value set and use it as the second minimum value;

[0025] S57, if the difference between the first minimum value and the second minimum value is not greater than a preset threshold, the combination of environmental parameters corresponding to the second minimum value is taken as the extreme environmental parameter combination.

[0026] According to the embodiments of this application, the above-mentioned technical solution of this application has at least the following beneficial effects: by hierarchically screening the minimum objective function value, iteratively constructing new environmental parameter combinations and updating the first minimum value, and using whether the difference between two minimum values ​​meets a preset threshold as the convergence criterion, it can gradually and accurately approach the extreme working conditions of ship positioning, ensuring the solution accuracy of the extreme environmental parameter combinations. At the same time, by adopting a proportional sampling iteration method instead of full enumeration traversal, the computational scale is effectively controlled, the solution time is greatly reduced, and the convergence logic is clear and controllable, which can stably and efficiently lock the worst environmental parameter combinations, providing reliable support for the accurate assessment of ship positioning capabilities.

[0027] In one possible implementation of the first aspect above, if the difference between the first minimum and the second minimum is greater than a threshold, the second minimum is updated to the first minimum, the second objective function value set is updated to the first objective function value set, and iterative steps S52-S56 are repeated until the difference between the minimum values ​​of two adjacent iterations is not greater than the threshold. The combination of environmental parameters corresponding to the second minimum obtained in the final iteration is taken as the limit combination of environmental parameters.

[0028] According to the embodiments of this application, the above-mentioned technical solution of this application has at least the following beneficial effects: by constructing a cyclical iterative convergence mechanism, it can gradually and accurately approach the worst extreme working conditions, effectively improving the solution accuracy of extreme positioning capability. At the same time, using the difference threshold as the iteration termination criterion can flexibly balance the solution accuracy and computational cost, ensuring that the solution process is stable and controllable, and ensuring that the final ship positioning capability assessment result is accurate and reliable.

[0029] In one possible implementation of the first aspect above, a second set of environment parameters is constructed based on the combination of environment parameters corresponding to the objective function values ​​in the seed set of objective function values, including:

[0030] Based on the combination of environmental parameters corresponding to each objective function value in the seed set of objective function values, a second combination of environmental parameters is obtained through Markov Monte Carlo sampling.

[0031] According to the embodiments of this application, the above-mentioned technical solution of this application has at least the following beneficial effects: Based on the critical environmental parameter combination obtained by screening, a second environmental parameter combination is generated by the Markov Monte Carlo sampling method, which can carry out directional sampling around the critical working condition area of ​​the ship positioning limit, accurately focus on the limit capability boundary interval, avoid redundant calculation caused by random sampling in the whole space, and significantly improve the effectiveness and pertinence of the sample.

[0032] In one possible implementation of the first aspect above, the thrust distribution result of the ship under various combinations of environmental parameters is determined, including:

[0033] Each combination of environmental parameters is input into a pre-defined ship thrust quadratic programming model to obtain the thrust allocation results.

[0034] According to the embodiments of this application, the above-mentioned technical solution of this application has at least the following beneficial effects: the use of a preset ship thrust quadratic programming model to solve the thrust allocation results corresponding to each combination of environmental parameters can provide accurate and reliable input for subsequent dynamic positioning status evaluation and objective function calculation, adapt to the iterative solution process of subset simulation, and ensure the computational efficiency and evaluation accuracy of the overall analysis of ship positioning capability.

[0035] In one possible implementation of the first aspect above, a dynamic positioning state evaluation is performed on each thrust allocation result to obtain an evaluation result corresponding to each thrust allocation result, including:

[0036] The results of each thrust distribution are used as input data for a preset dynamic positioning factor function to obtain the evaluation results.

[0037] According to the embodiments of this application, the above-mentioned technical solution of this application has at least the following beneficial effects: the evaluation result is obtained by calculating the thrust distribution result using a preset dynamic positioning factor function, which transforms the determination of the ship's dynamic positioning status into a standardized quantitative calculation, ensuring that the positioning status evaluation standard is unified and the result is objective and accurate, and avoiding the subjective bias of qualitative judgment.

[0038] Secondly, this application provides a ship positioning capability determination device based on subset simulation, comprising:

[0039] The combined construction module is used to obtain a combination of multiple environmental parameters experienced by the ship. The combination of environmental parameters includes at least wind speed, the angle between wind direction and ship heading, the angle between current direction and ship heading, and the angle between wave direction and ship heading.

[0040] The thrust calculation module is used to determine the thrust allocation result of the ship under various combinations of environmental parameters. The thrust allocation result includes executable thrust allocation schemes or no executable thrust allocation schemes.

[0041] The evaluation and determination module is used to evaluate the dynamic positioning status of each thrust allocation result and obtain the evaluation result corresponding to each thrust allocation result. The evaluation result is used to indicate whether the ship can be positioned.

[0042] The objective function calculation module is used to take each combination of environmental parameters and its corresponding evaluation results as input to a preset objective function to obtain the objective function value corresponding to each combination of environmental parameters. The objective function is used to characterize whether the ship has omnidirectional positioning capability under the current wind speed.

[0043] The output module is used to optimize the ship's positioning based on the objective function value using a subset simulation optimization method, thereby obtaining the combination of extreme environmental parameters for the ship to maintain its positioning, and determining the ship's extreme positioning capability based on the combination of extreme environmental parameters.

[0044] Thirdly, this application provides an electronic device including a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement the method for determining ship positioning capability based on subset simulation as disclosed in the first aspect and any possible implementation thereof.

[0045] Fourthly, this application provides a computer-readable storage medium storing at least one instruction or at least one program, wherein the at least one instruction or at least one program is loaded and executed by a processor to implement the method for determining ship positioning capability based on subset simulation as disclosed in the first aspect and any possible implementation thereof.

[0046] Fifthly, this application provides a computer program product comprising: computer instructions that, when executed on an electronic device, cause the electronic device to perform the method for determining ship positioning capabilities based on subset simulation as disclosed in the first aspect and any possible implementation thereof.

[0047] The beneficial effects of the second to fifth aspects can be found in the first aspect and the beneficial effects of any possible implementation of the first aspect, and will not be repeated here. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the ship's coordinate system in the embodiments of this application;

[0049] Figure 2 This is a linearized schematic diagram of the feasible region of the thrust convexity of the azimuth thruster in the embodiments of this application.

[0050] Figure 3 This is a linearized schematic diagram of the non-convex feasible region of the azimuth thruster in the embodiments of this application.

[0051] Figure 4 This is a flowchart illustrating the process of determining a ship's positioning capability in an embodiment of this application.

[0052] Figure 5 This is a flowchart of the subset optimization process in the embodiments of this application;

[0053] Figure 6 This is a box plot of the optimal solution in the embodiments of this application as a function of the number of computation layers;

[0054] Figure 7 This is a graph showing the change of the optimal solution after 50 repeated calculations in the embodiments of this application.

[0055] Figure 8 This is a flowchart illustrating the overall implementation of the method in the embodiments of this application;

[0056] Figure 9 This is a diagram showing the wind, wave, and current curves with the downward limiting wind speed in the embodiments of this application.

[0057] Figure 10 This is a structural block diagram of the ship positioning capability determination device in the embodiments of this application;

[0058] Figure 11 This is a block diagram of the electronic device in the embodiments of this application;

[0059] Figure 12 This is a block diagram of a system-on-chip (SoC) in the embodiments of this application. Detailed Implementation

[0060] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0061] The following is in conjunction with the appendix Figure 1-3 An overview of the thruster deployment and detailed information of the embodiments of this application is provided.

[0062] refer to Figures 1-3 , Figure 1 A schematic diagram of the ship's coordinate system in an embodiment of this application is shown. Figure 2 This paper shows a linearized schematic diagram of the feasible region for the thrust convexity of the azimuth thruster in an embodiment of this application. Figure 3 A schematic diagram illustrating the linearization of the non-convex feasible region of thrust for a full-rotation thruster in an embodiment of this application is shown.

[0063] like Figure 1 As shown, the center point of the ship is taken as the origin of the coordinate system. The X-axis (longitudinal axis) is the direction from the origin along the ship's length towards the bow, and the Y-axis (transverse axis) is the direction from the origin along the ship's width towards the starboard side. The three lateral thrusters T1, T2, and T3 are arranged sequentially at the bow along the X-axis, while the three azimuth thrusters T4, T5, and T6 are arranged in an equilateral triangle at the stern.

[0064]

[0065] As shown in Table 1, taking a ship with a length of 168 meters and a beam of 39.8 meters as an example, its draft is 7.5 meters, its displacement is 40,924 tons, its frontal windward area is 1,150 square meters, its side windward area is 2,450 square meters, and its stern drag force is 350 kN. Therefore, the coordinates of T1~T6 are (76.2, 0), (72.6, 0), (67.2, 0), (-77.4, -14.0), (-80.4, 0), and (-77.4, 14), respectively. The power of T1~T3 is 3000 kW, and there is no thrust exclusion zone. The power of T4~T6 is 4000 kW, and the central angle of T4 in thrust exclusion zone 1 is -77.91°, with a range of ±19.99°, while the central angle of thrust exclusion zone 2 is -90°, with a range of ±15.67°. T5 has a central angle of 102.09° in thrust exclusion zone 1, ranging from ±19.99°, and a central angle of -102.09° in thrust exclusion zone 2, ranging from ±19.99°. T6 has a central angle of 90° in thrust exclusion zone 1, ranging from ±15.67°, and a central angle of 77.91° in thrust exclusion zone 2, ranging from ±19.99°.

[0066] For the lateral thrusters (T1~T3), the longitudinal thrust component is always 0, and only the lateral thrust component can be generated, i.e. , This is the maximum thrust. For azimuth thrusters (T4~T6), the longitudinal thrust component and the lateral thrust component should satisfy... , It represents the components of the thrust of the i-th thruster along the X and Y axes.

[0067] like Figure 2 As shown, when the thrust angle prohibition region of the azimuth thruster is not considered, the feasible region of the azimuth thruster is a circular region, which has nonlinear constraints. By approximating the circular boundary as multiple straight boundary lines, the nonlinear constraints can be simplified into linear constraints composed of a series of linear equations.

[0068] like Figure 3 As shown, when considering the thrust angle prohibition region of the azimuth thruster, the thrust feasible region of the azimuth thruster can be regarded as being composed of multiple sub-thrust feasible regions, and the constraint linearization can also be achieved.

[0069] The following is a brief overview of the relationship between wind speed, meaningful wave height, and spectral peak period.

[0070]

[0071] As shown in Table 2, as the wind speed experienced by the ship gradually increases from 0 knots to 68.09 knots, the significant wave height gradually increases from 0 m to 15.49 m, and the spectral peak period gradually increases from 0 s to 18.46 s. This demonstrates a direct proportional relationship between wind speed, significant wave height, and spectral peak period.

[0072] The technical problems to be solved by the embodiments of this application will be described below.

[0073] As described in the background technology section above, the analysis of ship dynamic positioning capability is a key part of the marine engineering equipment design stage. The core evaluation index is the combination of minimum extreme environmental parameters that the ship can withstand in all directions. If the evaluation results are biased, overestimating the positioning capability will compress the actual operation window and fail to guarantee the stability of the ship's position, while underestimating the positioning capability will cause redundancy in the power configuration of the propulsion and power system and increase the construction cost.

[0074] Both existing calculation schemes have shortcomings. The scheme that uses the simplified assumption of wind, waves and current in the same direction cannot cover the actual working conditions where wind, waves and current are in different directions, making it difficult to accurately match the worst combination of environmental parameters and resulting in insufficient evaluation accuracy. The scheme that uses the enumeration method to traverse combinations of different directions suffers from problems such as large computational load, long time consumption and low solution efficiency.

[0075] Therefore, to address the aforementioned issues, this application provides a method for determining ship positioning capability based on subset simulation. This method involves acquiring multiple sets of environmental parameter combinations, including wind speed, the angle between wind direction and ship heading, the angle between wave direction and ship heading, and the angle between current direction and ship heading. The method then solves for the thrust distribution of the ship under each combination and evaluates its dynamic positioning status. The environmental parameter combinations and corresponding evaluation results are input into an objective function to obtain function values. Finally, a subset simulation optimization method is used to obtain the limiting environmental parameter combinations that allow the ship to maintain its positioning, thereby determining the ship's limiting positioning capability.

[0076] It overcomes the simplistic assumption of wind, waves, and currents moving in the same direction, comprehensively covering actual operating conditions where wind, waves, and currents move in opposite directions. It accurately searches for the worst combination of environmental parameters, improving the accuracy of positioning capability assessment. At the same time, compared with the enumeration traversal method, it effectively reduces the amount of computation and solution time, improving analysis efficiency. It can avoid the problems of overestimating positioning capability and compressing the operating window, or underestimating it and causing power redundancy in propulsion and power systems and increased construction costs.

[0077] To better understand the ship positioning capability determination method based on subset simulation in the embodiments of this application, the following description is provided in conjunction with the appendix to the specification. Figure 4 - Figure 9 The specific solutions corresponding to the ship positioning capability determination method based on subset simulation in the embodiments of this application will be described in detail.

[0078] Reference Figure 4 , Figure 4 This is a flowchart illustrating the process of determining a ship's positioning capability in an embodiment of this application.

[0079] like Figure 4 As shown in the embodiments of this application, a method for determining ship positioning capability based on subset simulation includes S10-S50.

[0080] S10 is used to obtain a combination of multiple environmental parameters experienced by the ship.

[0081] The combination of environmental parameters may include at least wind speed, the angle between wind direction and ship heading, the angle between current direction and ship heading, and the angle between wave direction and ship heading.

[0082] In some embodiments, obtaining a combination of multiple environmental parameters experienced by the ship includes:

[0083] For each parameter in the environmental parameter combination, random sampling is performed within its corresponding preset search interval to obtain sampled values ​​that satisfy the preset probability distribution model corresponding to the parameter. The sampled values ​​of each parameter are then combined to obtain the environmental parameter combination.

[0084] Understandably, the above parameters can be wind speed, the angle between wind direction and ship heading, the angle between current direction and ship heading, and the angle between wave direction and ship heading.

[0085] In some embodiments, the Monte Carlo sampling method can be used to sample each parameter in the combination of environmental parameters.

[0086] It should be noted that other sampling methods can also be used to sample the parameters, such as the Latin hypercube sampling method. This paper does not restrict the specific sampling method.

[0087] In some embodiments, the above probability distribution model can be expressed as:

[0088]

[0089] Among them, V w p represents wind speed. v (V) w V represents the wind speed probability density function. lb V represents the lower limit of wind speed sampling. ub U[V] represents the upper limit of wind speed sampling. lb， V ub [Indicates wind speed at V] lb and V ub The values ​​are between (i.e., the search interval corresponding to wind speed), where φ represents the angle between the wind direction and the ship's heading, and p φ (φ) represents the probability density function of the angle between the wind direction and the ship's heading. lb φ represents the lower limit of the sampling value for the angle between the wind direction and the ship's heading. ub U[φ] represents the upper limit of the sampling angle between the wind direction and the ship's heading. lb， φ ub ] indicates the angle between the wind direction and the ship's heading at φ. lb and φ ub The value is taken between (i.e., the search interval corresponding to the angle between the wind direction and the ship's heading). Indicates the angle between the direction of the current and the heading of the ship. The probability density function representing the angle between the flow direction and the ship's bow direction. This represents the lower limit of the sampling value for the angle between the flow direction and the ship's bow. This represents the upper limit of the sampling angle between the flow direction and the ship's heading. The angle between the current direction and the ship's heading is... and The range of values ​​(i.e., the search interval corresponding to the angle between the current direction and the ship's heading), where β represents the angle between the wave direction and the ship's heading, and p β (β) represents the probability density function of the angle between the wave direction and the ship's heading. lb β represents the lower limit of the sampling value for the angle between the wave direction and the ship's bow direction. ub U[β] represents the upper limit of the sampling angle between the wave direction and the ship's bow direction. lb， βub ] indicates the angle between the wave direction and the ship's heading at β. lb and β ub The value is taken from the range between the wave direction and the ship's heading (i.e., the search range corresponding to the angle between the wave direction and the ship's heading).

[0090] Understandably, obtaining multiple sets of environmental parameters, including the angle between wind speed, wind direction and ship heading, the angle between current direction and ship heading, and the angle between wave direction and ship heading, can break the simplistic assumption of wind, waves and current being in the same direction, restore the real multi-directional coupling conditions of the ocean, provide comprehensive and realistic operating condition inputs for subsequent analysis, and ensure the operating condition adaptability of the assessment results from the source.

[0091] S20 determines the thrust distribution of the ship under various combinations of environmental parameters.

[0092] The thrust allocation result includes either an executable thrust allocation scheme or no executable thrust allocation scheme.

[0093] In some embodiments, the combinations of environmental parameters are input into a preset ship thrust quadratic programming model to obtain the thrust allocation results.

[0094] In some embodiments, the quadratic programming model for ship thrust is as follows:

[0095]

[0096] st

[0097]

[0098]

[0099]

[0100]

[0101] Where u is the design variable composed of all thruster thrust components. , Let P be the feasible region for the thrust of the i-th thruster, and let P be a diagonal matrix representing the weights of each thrust component. i y i Let be the coordinates of the i-th thruster. The ship is subjected to total external longitudinal forces. The ship is subjected to a total external lateral force. The ship is subjected to the total external bow rolling moment. For longitudinal wind force, It is a crosswind. For wind torque, For longitudinal wave force, For lateral wave force, For wave torque, For longitudinal flow force, For lateral flow force, For the flow torque, For other longitudinal forces, For other lateral forces, For other torques, It is air density. He is the captain, A x It is the frontal windward area, A y It is the side windward area, α x For the longitudinal wind load factor, α y α is the lateral wind load factor. m This is the wind moment coefficient. It is the density of seawater, A cx For the frontal airflow area, A cy For the lateral airflow area, γ x γ is the longitudinal flow load factor. y γ is the transverse flow load factor. m The flow moment coefficient, There is a high-pitched wave. It is the spectral peak period. It is angular frequency. It is the wave spectral density function, χ x For longitudinal wave force, χ y For lateral wave force, χ m This refers to wave torque.

[0102] Understandably, solving for the thrust distribution results corresponding to various combinations of environmental parameters can accurately verify the feasibility of the thrust output of the ship's propulsion system under the corresponding operating conditions, quickly determine whether there is an executable thrust scheme, and provide direct quantitative basis for positioning capability assessment.

[0103] S30, perform dynamic positioning status evaluation on each thrust allocation result to obtain the evaluation result corresponding to each thrust allocation result.

[0104] The evaluation results are used to indicate whether a ship can be positioned.

[0105] In some embodiments, each thrust allocation result can be used as input data for a preset dynamic positioning factor function to obtain evaluation results.

[0106] The expression for the dynamic positioning factor function is as follows:

[0107]

[0108] Among them, I DPThis is the function expression for the dynamic positioning factor, provided that the thrust allocation result outputs an executable thrust allocation scheme. =1, in the case where the thrust allocation result outputs that there is no executable thrust scheme. =10000.

[0109] Understandably, conducting a dynamic positioning status evaluation on the thrust allocation results can transform the feasibility of thrust allocation into a standardized positioning capability judgment conclusion, achieving a unified evaluation of positioning performance under various working conditions, and providing clear judgment input for subsequent calculations.

[0110] S40: Each combination of environmental parameters and its corresponding evaluation results are used as inputs to a preset objective function to obtain the objective function value corresponding to each combination of environmental parameters.

[0111] The objective function is used to characterize whether the ship has omnidirectional positioning capability under the current wind speed.

[0112] The objective function expression is as follows:

[0113]

[0114] It is understandable that by inputting the combination of environmental parameters and the corresponding evaluation results into the objective function to obtain the function value, a quantitative mapping relationship between environmental parameters and omnidirectional positioning capability can be established, enabling horizontal comparison and ranking of positioning capabilities under different working conditions, and providing a numerically processable optimization objective for subsequent optimization solutions.

[0115] S50, based on the objective function value, is optimized using a subset simulation optimization method to obtain the combination of extreme environmental parameters for maintaining the ship's positioning.

[0116] The ship's extreme positioning capability is determined based on the combination of extreme environmental parameters.

[0117] Understandably, iteratively solving for the combination of extreme environment parameters through subset simulation optimization can replace the full traversal mode of the traditional enumeration method, significantly reducing the amount of computation and solution time. At the same time, it can accurately converge to the worst extreme working condition in which the ship can maintain its positioning, ensuring the accuracy of the assessment of the extreme positioning capability. This avoids compressing the actual operating window due to overestimation of capability and failing to guarantee the stability of the ship's position, and also prevents redundancy in the power configuration of the propeller and electric system due to underestimation of capability, thereby reducing the cost of ship construction.

[0118] The following is a detailed explanation of step S50.

[0119] refer to Figure 5 , Figure 5 A flowchart illustrating subset optimization in an embodiment of this application is shown.

[0120] like Figure 5 As shown in the embodiment of this application, based on the objective function value, the combination of extreme environmental parameters for maintaining the ship's positioning is obtained by optimization through subset simulation optimization method, including steps S51-S56.

[0121] In step S51, a first set of objective function values ​​is constructed based on the objective function values, and the minimum value is extracted from the first set of objective function values ​​as the first minimum value.

[0122] Understandably, extracting the minimum value of all objective function values ​​can quickly determine the worst working condition in the initial sample set, which can then be used as the starting point for iteration.

[0123] S52, according to the preset sampling ratio, select the smallest number of objective function values ​​corresponding to the sampling ratio from the first objective function value set to obtain the objective function value seed set.

[0124] For example, if the sampling ratio is p0, all objective function values ​​are sorted in ascending order, and the first p0 objective function values ​​are taken as the seed set of objective function values, which are used as the input data for the next step.

[0125] Understandably, by selecting the minimum objective function value according to the preset sampling ratio, valid working condition samples near the limit boundary can be retained, while redundant samples far from the failure boundary can be eliminated, thus avoiding invalid samples from participating in the calculation, increasing the amount of computation, and improving the solution efficiency.

[0126] S53: Select the maximum value from the seed set of objective function values ​​as the critical value.

[0127] S54. Construct a second set of environmental parameters based on the environmental parameter combinations corresponding to the objective function values ​​in the objective function value seed set.

[0128] In some embodiments, a second set of environmental parameters is obtained by using the Markov Monte Carlo sampling method based on the combination of environmental parameters corresponding to each objective function value in the objective function value seed set.

[0129] For example, if the number of environmental parameter combinations in step S10 is N, then the number of environmental parameter combinations corresponding to each function value in the objective function value seed set is p0×N. By using the Markov Monte Carlo sampling method, a Markov chain of length 1 / p0 is generated for each minimum function value corresponding to the environmental parameter combination. In this way, N second environmental parameter combinations can be generated.

[0130] Understandably, by constructing a second set of environmental parameters based on the selected critical samples, directional sampling can be carried out around the identified extreme boundary regions. By keeping the number of samples constant through sampling methods, the solution range can be gradually narrowed towards the actual extreme conditions, avoiding a large amount of invalid calculations caused by random sampling of the entire parameter space.

[0131] S55, calculate the objective function value corresponding to each combination of second environmental parameters to obtain the set of second objective function values.

[0132] It should be noted that the method for calculating the objective function value here can be found in the above text, and will not be elaborated on here.

[0133] S56, if the objective function value in the second objective function value set is not greater than the critical value, extract the minimum value from the second objective function value set and use it as the second minimum value.

[0134] It should be noted that if the objective function value in the second objective function value set is greater than the critical value, it means that the generated second environment parameter combination does not meet the convergence condition. In this case, the second environment parameter combination needs to be regenerated. The specific process of regeneration can be referred to above, and will not be elaborated on here.

[0135] S57, if the difference between the first minimum value and the second minimum value is not greater than a preset threshold, the combination of environmental parameters corresponding to the second minimum value is taken as the extreme environmental parameter combination.

[0136] Understandably, using the minimum difference between two adjacent iterations not exceeding a preset threshold as the convergence output condition allows the calculation to be terminated in time when the solution accuracy meets the preset requirements, avoiding unnecessary iterations and achieving a balance between solution accuracy and computational cost.

[0137] S58, if the difference between the first minimum and the second minimum is greater than the threshold, update the second minimum to the first minimum, update the second objective function value set to the first objective function value set, and repeat the iteration steps S52-S56 until the difference between the minimum values ​​of two adjacent iterations is not greater than the threshold. The combination of environmental parameters corresponding to the second minimum obtained in the final iteration is taken as the limit combination of environmental parameters.

[0138] Understandably, when the convergence condition is not met, the first minimum value is updated and the sampling calculation steps are repeated. Through multiple rounds of iteration, the solution is continuously approached to the actual extreme conditions, gradually reducing the solution error and ensuring that the final output combination of extreme environment parameters has sufficient solution accuracy and result reliability.

[0139] Through the above steps S51-S58, the pain points of large computational volume and long time consumption of the traditional enumeration method are solved, and the defects of insufficient working condition coverage and evaluation result deviation caused by simplification assumptions are avoided. It can provide an efficient and reliable solution path for the accurate evaluation of the ship's limit positioning capability.

[0140] The following is for reference. Figures 6-7 , Figure 6The box plot of the optimal solution as a function of the number of computation layers in the embodiments of this application is shown. Figure 7 The graph shows the variation curve of the optimal solution after 50 repeated calculations in the embodiments of this application.

[0141] like Figure 6 As shown, the horizontal axis represents the number of Subset Simulation (SS) layers, corresponding to the iteration levels of the subset simulation in this application. Layer 0 is the initial environmental parameter sampling layer, layers 1 to 9 are the sample layers obtained by iterative iteration, and the rightmost GA group is the comparison result obtained by solving using the genetic algorithm.

[0142] The vertical axis represents the minimum value of the objective function, measured in knots. It indicates the ship's maximum wind speed obtained at the corresponding level. The smaller the value, the closer it is to the limit boundary of the ship's all-around positioning capability.

[0143] The figure shows the statistical distribution of the minimum objective function value of each box cell in the repeated experiments at the corresponding iteration level: the box covers the interquartile range of the data, the center line of the box is the median value of the data, the upper and lower extended whiskers are the extreme value range of the data, and the discrete dots are outlier data points.

[0144] As shown in the figure, with the increase of the number of SS iteration layers, the overall level of the objective function minimum gradually decreases, and the dispersion of the data distribution continues to narrow. The initial layer 0 samples correspond to random sampling in the full parameter space, with the extreme wind speed generally being high and having large dispersion. After multiple rounds of critical sample screening and directional sampling through subset simulation, the solution results gradually converge towards the minimum value. After the 7th layer, the distribution range tends to stabilize, and the dispersion is significantly reduced. This indicates that the iterative solution method of this application can gradually approach the worst extreme working condition, and the solution results have good stability.

[0145] Meanwhile, the solution results of the method in this application after multiple iterations tend to be consistent with the optimization results of the genetic algorithm (GA), which verifies the accuracy of the solution results of the ship positioning capability determination method based on subset simulation in this application.

[0146] like Figure 7 As shown, the horizontal axis represents the number of SS iterations, and the vertical axis represents the minimum value of the objective function, with units of knots. Multiple curves in the figure correspond to the single solution process of each independent repeated experiment, and the blue curve with a circular marker represents the average value of the results from 50 independent repeated experiments.

[0147] As shown in the figure, the minimum value of the objective function in each single experiment shows a monotonically decreasing trend with the increase of the number of iteration layers, gradually decreasing from the level of about 30 knots in the initial layer, and finally converging to about 28 knots.

[0148] The average curve of 50 tests shows a smooth downward trend, and the value tends to stabilize after the 7th to 9th layers without significant fluctuations. This trend indicates that the ship positioning capability determination method based on subset simulation in this application has excellent convergence characteristics. Multiple independent random tests can stably converge to a consistent limiting wind speed result, and the solution process is not significantly affected by the initial sampling random bias.

[0149] Meanwhile, the iterative process monotonically approaches the boundary of the extreme working condition, which conforms to the technical logic of gradually shrinking the critical solution region in subset simulation. It can efficiently and reliably search for the worst combination of extreme environmental parameters in the world, providing stable and accurate solution support for the assessment of the ship's extreme positioning capability.

[0150] The following is in conjunction with the appendix Figure 8 A brief overview of the overall implementation process of the method in the embodiments of this application is provided.

[0151] refer to Figure 8 , Figure 8 A flowchart illustrating the overall implementation of the method in an embodiment of this application is shown.

[0152] like Figure 8 As shown, the overall implementation process of the method in this application includes steps S100-S700.

[0153] S100 defines the probability distribution model for each parameter in the combination of algorithm parameters and environment parameters.

[0154] It should be noted that the algorithm parameters may include the sampling ratio mentioned above, as well as the number of combinations of environmental parameters.

[0155] S200 uses the Monte Carlo sampling method to sample each parameter, resulting in a combination of multiple environmental parameters.

[0156] S300 finds the first minimum value among all combinations of environmental parameters and determines the seed set and critical value of the objective function.

[0157] S400, construct the second combination of environmental parameters and calculate the corresponding set of second objective function values.

[0158] S500, if each objective function value in the second set of objective function values ​​is not greater than the critical value, determine the second minimum value from among them.

[0159] S600, determine whether the difference between the first minimum value and the second minimum value is less than or equal to a preset threshold.

[0160] If no, update the second critical value to the first critical value and iterate through steps S200-S600; if yes, proceed to step S700.

[0161] S700 uses the combination of environmental parameters corresponding to the second minimum value as the extreme environmental parameter combination.

[0162] The following is for reference. Figure 9 , Figure 9 The diagram shows the wind, wave, and current curves with the downward limiting wind speed in an embodiment of this application.

[0163] like Figure 9 As shown, the circumferential axis of the polar coordinates represents the azimuth angle of the environmental influence (unit: °), covering the entire circumference from 0° to 360°. The radial axis represents the limiting wind speed (unit: knots) that the ship can stably withstand. The blue closed curves in the figure are the limiting wind speed envelopes corresponding to each azimuth angle under the assumption that wind, waves, and current are in the same direction. The area enclosed by the envelope is the operating range in which the ship can maintain dynamic positioning stability.

[0164] The red marker corresponds to the global minimum limiting wind speed under the traditional wind, wave and current co-directional calculation scheme, with a value of 29.9 knots. The corresponding environmental direction is 90.0°, which is the positioning capability limit under the worst co-directional working condition that can be obtained by the traditional simplified method.

[0165] The pink markers correspond to the global minimum limiting wind speed obtained by optimizing the ship positioning capability determination method based on subset simulation in this application within the full parameter space with different wind, wave, and current directions. The value is 27.8 knots, corresponding to the extreme environmental parameter combination of wind direction 50.0°, wave direction 89.9°, and current direction 79.8°. This operating condition is a severe condition with multi-directional coupling of wind, waves, and current. Its tolerable limiting wind speed is lower than the minimum value under the assumption of wind, wave, and current in the same direction, making it a more stringent extreme condition in actual operations.

[0166] This comparison clearly demonstrates that traditional calculation schemes relying on the simplified assumption of wind, waves, and current moving in the same direction cannot cover harsh operating conditions where wind, waves, and currents move in opposite directions, and are prone to overestimating the actual positioning capability of ships. The method in this application overcomes the limitations of the same-direction assumption, efficiently traversing all combinations of operating conditions with different wind, wave, and current directions through subset simulation. It accurately searches for the most severe combination of extreme environmental parameters globally, resulting in extreme positioning capability results that better reflect actual marine operation scenarios. This effectively avoids the problems of compressing the operational window due to overestimation of positioning capability and failing to guarantee ship position stability. Simultaneously, it provides accurate and reliable quantitative basis for ship propulsion system configuration and operational safety boundary delineation.

[0167] refer to Figure 10 , Figure 10 A structural block diagram of the ship positioning capability determination device in an embodiment of this application is shown.

[0168] like Figure 10As shown, this application provides a ship positioning capability determination device 1000 based on subset simulation, including: a combination construction module 1010, a thrust calculation module 1020, an evaluation determination module 1030, an objective function calculation module 1040, and an output module 1050.

[0169] The combined construction module 1010 is used to obtain a combination of multiple environmental parameters experienced by the ship. The combination of environmental parameters includes at least wind speed, the angle between wind direction and ship heading, the angle between current direction and ship heading, and the angle between wave direction and ship heading.

[0170] The thrust calculation module 1020 is used to determine the thrust allocation result of the ship under various combinations of environmental parameters. The thrust allocation result includes executable thrust allocation schemes or no executable thrust allocation schemes.

[0171] The evaluation and determination module 1030 is used to evaluate the dynamic positioning status of each thrust distribution result and obtain the evaluation result corresponding to each thrust distribution result. The evaluation result is used to indicate whether the ship can be positioned.

[0172] The objective function calculation module 1040 is used to take each combination of environmental parameters and its corresponding evaluation results as input to a preset objective function to obtain the objective function value corresponding to each combination of environmental parameters. The objective function is used to characterize whether the ship has omnidirectional positioning capability under the current wind speed.

[0173] The output module 1050 is used to optimize the ship's positioning based on the objective function value using a subset simulation optimization method, thereby obtaining the combination of extreme environmental parameters for the ship to maintain its positioning, and determining the ship's extreme positioning capability based on the combination of extreme environmental parameters.

[0174] This application provides an electronic device, which includes a processor and a memory. The memory stores at least one instruction or at least one program. When the processor loads and executes the instruction or program, the electronic device performs the ship positioning capability determination method based on subset simulation described in the above embodiments. Its specific functions and corresponding technical effects can be found in the above embodiments. Figures 1-9 The method for determining ship positioning capabilities based on subset simulation, as explained above, will not be repeated here. The following section will combine... Figure 11 The electronic devices described in the embodiments of this application will be described in detail.

[0175] refer to Figure 11 , Figure 11A block diagram of an electronic device 1200 according to an embodiment of this application is shown. The electronic device 1200 may include one or more processors 1201 coupled to a controller hub 1203. In at least one embodiment, the controller hub 1203 communicates with the processor 1201 via a multi-branch bus such as a front side bus (FSB) 1210, a point-to-point interface such as a quick path interconnect (QPI), or a similar connection. The processor 1201 executes instructions controlling general types of data processing operations. In one embodiment, the controller hub 1203 includes, but is not limited to, a graphics memory controller hub (GMCH) (not shown) and an input / output hub (IOH) (which may be on a separate chip) (not shown), wherein the GMCH includes memory and a graphics controller and is coupled to the IOH.

[0176] Electronic device 1200 may also include a coprocessor 1202 and a memory 1204 coupled to a controller hub 1203. Alternatively, one or both of the memory and the GMCH may be integrated within the processor (as described in this application), with memory 1204 and coprocessor 1202 directly coupled to processor 1201 and controller hub 1203, which resides on a single chip with the IOH. Memory 1204 may be, for example, dynamic random access memory (DRAM), phase change memory (PCM), or a combination of both. In one embodiment, coprocessor 1202 is a dedicated processor, such as, for example, a high-throughput MIC (many integerized core) processor, a network or communication processor, a compression engine, a graphics processor, a general-purpose computing on GPU (GPGPU), or an embedded processor, etc. Optional properties of coprocessor 1202 are indicated by dashed lines. Figure 11 middle.

[0177] As a computer-readable storage medium, memory 1204 may include one or more tangible, non-transitory computer-readable media for storing data and / or instructions. For example, memory 1204 may include any suitable non-volatile memory such as flash memory and / or any suitable non-volatile storage device such as one or more hard-disk drives (HDDs), one or more compact disc (CD) drives, and / or one or more digital versatile disc (DVD) drives.

[0178] In one embodiment, electronic device 1200 may further include a network interface controller (NIC) 1206. The network interface 1206 may include a transceiver for providing a radio interface for electronic device 1200 to communicate with any other suitable device, such as a front-end module, antenna, etc. In various embodiments, the network interface 1206 may be integrated with other components of electronic device 1200. The network interface 1206 can implement the functions of the communication unit in the above embodiments.

[0179] Electronic device 1200 may further include I / O device 1205. I / O device 1205 may include: a user interface designed to enable a user to interact with electronic device 1200; a peripheral component interface designed to enable peripheral components to also interact with electronic device 1200; and / or sensors designed to determine environmental conditions and / or location information related to electronic device 1200.

[0180] It is worth noting that, Figure 11 This is merely an example. That is, although... Figure 11 The electronic device 1200 shown includes multiple devices such as a processor 1201, a coprocessor 1202, a controller hub 1203, and a memory 1204. However, in practical applications, devices using the methods of this application may include only a portion of the devices in the electronic device 1200. For example, it may include only the processor 1201 and the network interface 1206. Figure 11 The properties of the optional devices are shown in dashed lines. According to some embodiments of this application, the memory 1204, which is a computer-readable storage medium, stores instructions or programs that, when executed on a computer, perform the ship positioning capability determination method based on subset simulation described in the above embodiments. Specific details can be found in the methods described in the above embodiments, and will not be repeated here.

[0181] Now for reference Figure 12The diagram shown is a block diagram of a system-on-chip (SoC) 1300 according to an embodiment of this application. Figure 12 In the diagram, similar components share the same reference numerals. Additionally, dashed boxes are an optional feature for more advanced SoCs. Figure 12 In this embodiment, the system-on-a-chip 1300 includes: an interconnect unit 1350 coupled to an application processor 1310; a system proxy unit 1380; a bus controller unit 1390; an integrated memory controller unit 1340; a group or one or more coprocessors 1320, which may include integrated graphics logic, an image processor, an audio processor, and a video processor; a static random access memory (SRAM) unit 1330; and a direct memory access (DMA) unit 1360. In one embodiment, the coprocessor 1320 includes a dedicated processor, such as, for example, a network or communication processor, a compression engine, a GPGPU, a high-throughput MIC processor, or an embedded processor.

[0182] The static random access memory unit 1330 may include one or more computer-readable media for storing data and / or instructions. The computer-readable storage medium may store instructions, specifically, temporary and permanent copies of those instructions. These instructions may include, when executed by at least one unit in the processor, causing the on-chip system 1300 to perform the ship positioning capability determination method based on subset simulation according to the above embodiments, specifically referring to the methods in the above embodiments, which will not be repeated here.

[0183] This application provides a computer-readable storage medium storing at least one instruction or at least one program. The instruction or program is loaded and executed by a processor to implement the ship positioning capability determination method based on subset simulation described in the above embodiments. Its specific functions and corresponding technical effects can be found in the above embodiments. Figures 1-9 The method for determining ship positioning capabilities based on subset simulation, as explained above, will not be elaborated upon here.

[0184] This application provides a computer program product, including computer instructions. When the computer instructions are executed on an electronic device, the electronic device causes the electronic device to implement the ship positioning capability determination method based on subset simulation described in the above embodiments. Its specific functions and corresponding technical effects can be found in the above embodiments. Figures 1-9 The method for determining ship positioning capabilities based on subset simulation, as explained above, will not be elaborated upon here.

[0185] Various embodiments of the mechanisms disclosed in this application can be implemented in hardware, software, firmware, or combinations of these implementation methods. Embodiments of this application can be implemented as computer programs or program code executable on a programmable system, the programmable system including at least one processor, a storage system (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device.

[0186] Program code can be applied to input instructions to execute the functions described in this application and generate output information. The output information can be applied to one or more output devices in a known manner. For the purposes of this application, the processing system includes any system having a processor such as, for example, a digital signal processor (DSP), a microcontroller, an application-specific integrated circuit (ASIC), or a microprocessor.

[0187] The program code can be implemented using a high-level procedural language or an object-oriented programming language to communicate with the processing system. Assembly language or machine language can also be used when needed. In fact, the mechanisms described in this application are not limited to any particular programming language. In either case, the language can be a compiled language or an interpreted language.

[0188] In some cases, the disclosed embodiments may be implemented in hardware, firmware, software, or any combination thereof. The disclosed embodiments may also be implemented as instructions carried or stored thereon on one or more temporary or non-temporary machine-readable (e.g., computer-readable) storage media, which may be read and executed by one or more processors. For example, the instructions may be distributed via a network or through other computer-readable media. Therefore, machine-readable media may include any mechanism for storing or transmitting information in a machine-readable (e.g., computer-readable) form, including but not limited to floppy disks, optical disks, CD-ROMs, compact disc read-only memory (CD-ROMs), magneto-optical disks, read-only memory (ROM), random access memory (RAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic cards or optical cards, flash memory, or tangible machine-readable storage for transmitting information (e.g., carrier waves, infrared signals, digital signals, etc.) using the Internet in the form of electrical, optical, acoustic, or other forms of propagated signals. Therefore, machine-readable media include any type of machine-readable medium suitable for storing or transmitting electronic instructions or information in a machine-readable (e.g., computer-readable) form.

[0189] In the accompanying drawings, some structural or methodological features may be shown in a specific arrangement and / or order. However, it should be understood that such a specific arrangement and / or order may not be necessary. Rather, in some embodiments, these features may be arranged in a manner and / or order different from that shown in the accompanying drawings. Furthermore, including structural or methodological features in a particular figure does not imply that such features are required in all embodiments, and in some embodiments, these features may be omitted or may be combined with other features.

[0190] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0191] It should be noted that all units / modules mentioned in the device embodiments of this application are logical units / modules. Physically, a logical unit / module can be a physical unit / module, a part of a physical unit / module, or a combination of multiple physical units / modules. The physical implementation of these logical units / modules themselves is not the most important factor; the combination of functions implemented by these logical units / modules is the key to solving the technical problems proposed in this application. Furthermore, to highlight the innovative aspects of this application, the above-described device embodiments of this application have not introduced units / modules that are not closely related to solving the technical problems proposed in this application. This does not mean that the above-described device embodiments do not contain other units / modules.

[0192] It should be noted that in the examples and description of this application, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0193] Although this application has been illustrated and described with reference to certain preferred embodiments thereof, those skilled in the art should understand that various changes in form and detail may be made thereto without departing from the spirit and scope of this application.

Claims

1. A method for determining ship positioning capability based on subset simulation, characterized in that, include: The system acquires a combination of multiple environmental parameters experienced by the ship, wherein the combination of environmental parameters includes at least wind speed, the angle between wind direction and ship heading, the angle between current direction and ship heading, and the angle between wave direction and ship heading. Determine the thrust allocation result of the ship under each of the aforementioned combinations of environmental parameters, wherein the thrust allocation result includes an executable thrust allocation scheme or no executable thrust allocation scheme exists; Each of the thrust allocation results is evaluated for dynamic positioning status to obtain an evaluation result corresponding to each thrust allocation result. The evaluation result is used to indicate whether the ship can be positioned. Each combination of environmental parameters and its corresponding evaluation result are used as input to a preset objective function to obtain the objective function value corresponding to each combination of environmental parameters. The objective function is used to characterize whether the ship has omnidirectional positioning capability under the current wind speed. Based on the objective function value, the ship is optimized using a subset simulation optimization method to obtain the extreme environmental parameter combination for maintaining its position. The ship's extreme positioning capability is then determined based on the extreme environmental parameter combination. The optimization based on the objective function value, using a subset simulation optimization method, yields the combination of extreme environmental parameters for maintaining the ship's positioning, including: S51, Based on the objective function value, construct a first objective function value set, and extract the minimum value from the first objective function value set as the first minimum value; S52, according to the preset sampling ratio, select the smallest number of objective function values ​​corresponding to the sampling ratio from the first objective function value set to obtain the objective function value seed set; S53, Select the maximum value from the seed set of the objective function values ​​as the critical value; S54, construct a second combination of environmental parameters based on the combination of environmental parameters corresponding to the objective function values ​​in the objective function value seed set; S55, calculate the objective function value corresponding to each combination of the second environmental parameters to obtain the set of second objective function values; S56, if the objective function value in the second objective function value set is not greater than the critical value, extract the minimum value from the second objective function value set as the second minimum value; S57, if the difference between the first minimum value and the second minimum value is not greater than a preset threshold, the combination of environmental parameters corresponding to the second minimum value is taken as the extreme environmental parameter combination.

2. The method according to claim 1, characterized in that, The acquisition of multiple environmental parameter combinations experienced by the ship includes: For each parameter in the combination of environmental parameters, random sampling is performed within its corresponding preset search interval to obtain sampled values ​​that satisfy the preset probability distribution model corresponding to the parameter; The environmental parameter combination is obtained by combining the sampled values ​​of each parameter.

3. The method according to claim 1, characterized in that, If the difference between the first minimum value and the second minimum value is greater than the threshold, the second minimum value is updated to the first minimum value, the second objective function value set is updated to the first objective function value set, and iterative steps S52-S56 are repeated until the difference between the minimum values ​​of two adjacent iterations is not greater than the threshold. The environmental parameter combination corresponding to the second minimum value obtained in the final iteration is taken as the extreme environmental parameter combination.

4. The method according to claim 1, characterized in that, The construction of a second set of environmental parameters based on the environmental parameter combinations corresponding to the objective function values ​​in the seed set of objective function values ​​includes: Based on the combination of environmental parameters corresponding to each objective function value in the seed set of objective function values, the second combination of environmental parameters is obtained by Markov Monte Carlo sampling method.

5. The method according to claim 1, characterized in that, The determination of the thrust distribution result of the ship under each of the aforementioned combinations of environmental parameters includes: Each of the aforementioned environmental parameter combinations is input into a preset ship thrust quadratic programming model to obtain the thrust allocation results for each.

6. The method according to claim 1, characterized in that, The step of evaluating the dynamic positioning status of each thrust allocation result to obtain an evaluation result corresponding to each thrust allocation result includes: The evaluation results are obtained by using each of the thrust allocation results as input data for a preset dynamic positioning factor function.

7. A device for determining ship positioning capability based on subset simulation, characterized in that, include: A combined construction module is used to obtain a combination of multiple environmental parameters experienced by the ship, wherein the combination of environmental parameters includes at least wind speed, the angle between wind direction and ship heading, the angle between current direction and ship heading, and the angle between wave direction and ship heading; The thrust calculation module is used to determine the thrust allocation result of the ship under each of the environmental parameter combinations, wherein the thrust allocation result includes an executable thrust allocation scheme or no executable thrust scheme. The evaluation and determination module is used to evaluate the dynamic positioning status of each of the thrust allocation results and obtain the evaluation result corresponding to each of the thrust allocation results. The evaluation result is used to indicate whether the ship can be positioned. The objective function calculation module is used to take each combination of environmental parameters and its corresponding evaluation results as input to a preset objective function to obtain the objective function value corresponding to each combination of environmental parameters. The objective function is used to characterize whether the ship has omnidirectional positioning capability under the current wind speed. The output module is used to optimize the objective function value using a subset simulation optimization method to obtain the combination of extreme environmental parameters for the ship to maintain its positioning, and to determine the ship's extreme positioning capability based on the combination of extreme environmental parameters. The optimization based on the objective function value, using a subset simulation optimization method, yields the combination of extreme environmental parameters for maintaining the ship's positioning, including: S51, Based on the objective function value, construct a first objective function value set, and extract the minimum value from the first objective function value set as the first minimum value; S52, according to the preset sampling ratio, select the smallest number of objective function values ​​corresponding to the sampling ratio from the first objective function value set to obtain the objective function value seed set; S53, Select the maximum value from the seed set of the objective function values ​​as the critical value; S54, construct a second combination of environmental parameters based on the combination of environmental parameters corresponding to the objective function values ​​in the objective function value seed set; S55, calculate the objective function value corresponding to each combination of the second environmental parameters to obtain the set of second objective function values; S56, if the objective function value in the second objective function value set is not greater than the critical value, extract the minimum value from the second objective function value set as the second minimum value; S57, if the difference between the first minimum value and the second minimum value is not greater than a preset threshold, the combination of environmental parameters corresponding to the second minimum value is taken as the extreme environmental parameter combination.

8. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the ship positioning capability determination method based on subset simulation as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction or at least one program, which is loaded and executed by a processor to implement the ship positioning capability determination method based on subset simulation as described in any one of claims 1 to 6.

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