Ship outboard water pressure load indirect monitoring method and system

Abstract

The invention belongs to the technical field of ships. The invention provides a ship outboard water pressure load indirect monitoring method and system. The method comprises the steps that a finite element model used for accurately describing the structural characteristics and mechanical response of a target ship body is established, and a CFD model of the target ship body is established; outboard water pressure load distribution is calculated based on a CFD model, an influence coefficient matrix is established according to the outboard water pressure load distribution, and a relational expression between outboard water pressure loads and structural response data is established based on the influence coefficient matrix; and receiving structural response data measured by the sensors arranged at the optimal measuring points on the ship body, and obtaining a real-time outboard water pressure load based on the structural response data and relational inversion. According to the invention, an indirect measurement method is adopted to monitor the outboard water pressure load of the ship in real time, and the limitations that the ship body is damaged and the number of arranged sensors is large in a direct monitoring method are overcome.

Description

Technical Field

[0001] The present invention relates to the field of ship technology, and in particular to a method and system for indirectly monitoring the outboard water pressure load of a ship. Background Art

[0002] The outboard water pressure load refers to the pressure from the outboard water on the hull shell (side structure) of a ship when it is sailing or anchored in the water. The load formed by this pressure has an important impact on the strength and stability of the hull structure.

[0003] At present, the methods for determining the outboard water pressure load and its distribution are mainly based on normative methods based on experience and simple formulas, and simulation calculation methods based on fluid mechanics theory. However, both methods have certain limitations and cannot truly reflect the load conditions that the ship is subjected to during actual use. Direct measurement of outboard water pressure loads, such as using pressure sensors, is theoretically feasible, but faces many challenges in practical applications. For example, the sensors need to be installed by drilling holes in the structure, which will affect the structural strength; at the same time, for large structures such as the hull, the deployment of a large number of pressure sensors is not only costly, but also difficult to achieve full coverage.

[0004] It can be seen that how to efficiently and accurately monitor the ship's outboard water pressure load without damaging the hull structure strength is a technical problem that needs to be solved. Summary of the invention

[0005] In this regard, the present invention provides a method, system, electronic equipment, computer storage medium and computer program product for indirect monitoring of the outboard water pressure load of a ship to solve the above-mentioned technical problems.

[0006] The present invention discloses a method for indirectly monitoring the outboard water pressure load of a ship, the method comprising the following steps:

[0007] Establish a finite element model for accurately describing the structural characteristics and mechanical response of the target ship, and establish a CFD model of the target ship;

[0008] Calculating the outboard water pressure load distribution based on the CFD model, establishing an influence coefficient matrix according to the outboard water pressure load distribution, and establishing a relationship between the outboard water pressure load and the structural response data based on the influence coefficient matrix;

[0009] Structural response data measured by sensors arranged at optimal measuring points on the hull are received, and real-time outboard water pressure load is obtained by inversion based on the structural response data and the relationship.

[0010] Optionally, the influence coefficient matrix is ​​as follows:

[0011]

[0012] Where C is the influence coefficient matrix, n is the number of measuring points, m is the number of unit loads, and element c is mn It represents the structural response coefficient of the nth best measuring point under the unit load m;

[0013] The relationship between the outboard water pressure load and the structural response data is as follows:

[0014] R=C·F

[0015] Wherein, R is the structural response vector measured by the sensors at each of the optimal measuring points, and F is the real-time outboard water pressure load to be inverted.

[0016] Optionally, the obtaining of a real-time outboard water pressure load based on the structural response data and the relational expression by inversion comprises:

[0017] F=(C T C -1 C T R

[0018] In the formula, C T is the transposed matrix of the influence coefficient matrix C, (C T C) -1 C T is the pseudo-inverse matrix.

[0019] Optionally, the method further comprises:

[0020] The water pressure distribution information of the outer surface of the hull under different sea conditions is calculated using the CFD model, and the water pressure distribution information is fitted using a multidimensional function approximation algorithm to obtain a unified mathematical expression of the water pressure load on the entire ship, which is input into the finite element model as a unit load to obtain a full-field strain result;

[0021] According to the full-field strain result, the sensor layout is optimized using an intelligent optimization algorithm to obtain the layout information of the best measuring point, wherein the layout information includes the best measuring point position and the best measuring point direction;

[0022] The influence coefficient matrix is ​​constructed using the optimized layout information of the sensors.

[0023] In some embodiments, the use of an intelligent optimization algorithm to optimize the sensor layout to obtain the layout information of the best measurement points includes:

[0024] The full-field strain results are analyzed and processed using a sensor layout optimization model based on a convolutional neural network to obtain a number of target layout areas and corresponding optimal measuring point directions, and a first number of the optimal measuring point positions are selected in each of the target layout areas; wherein the target layout area refers to an area on the outer surface of the hull of the target ship that is sensitive to the structural response;

[0025] The sensor layout optimization model also outputs a number of predicted non-target deployment areas and corresponding optimal measurement point directions, and selects a second number of the optimal measurement point positions in each of the non-target deployment areas; wherein the non-target deployment areas are located within a preset distance around the target deployment area.

[0026] The present invention also provides an indirect monitoring system for outboard water pressure load of a ship, the system comprising a plurality of sensors, a processor and a memory; the processor calls the computer program code in the memory to execute the following steps:

[0027] Establish a finite element model for accurately describing the structural characteristics and mechanical response of the target ship, and establish a CFD model of the target ship;

[0028] Calculating the outboard water pressure load distribution based on the CFD model, establishing an influence coefficient matrix according to the outboard water pressure load distribution, and establishing a relationship between the outboard water pressure load and the structural response data based on the influence coefficient matrix;

[0029] Structural response data measured by sensors arranged at optimal measuring points on the hull are received, and real-time outboard water pressure load is obtained by inversion based on the structural response data and the relationship.

[0030] Optionally, the influence coefficient matrix is ​​as follows:

[0031]

[0032] Where C is the influence coefficient matrix, n is the number of measuring points, m is the number of unit loads, and element c is mn It represents the structural response coefficient of the nth best measuring point under the unit load m;

[0033] The relationship between the outboard water pressure load and the structural response data is as follows:

[0034] R=C·F

[0035] Wherein, R is the structural response vector measured by the sensors at each of the optimal measuring points, and F is the real-time outboard water pressure load to be inverted.

[0036] Optionally, the obtaining of a real-time outboard water pressure load based on the structural response data and the relational expression by inversion comprises:

[0037] F=(C T C) -1 C T R

[0038] In the formula, C T is the transposed matrix of the influence coefficient matrix C, (C T C) -1 C T is the pseudo-inverse matrix.

[0039] Optionally, it also includes:

[0040] The water pressure distribution information of the outer surface of the hull under different sea conditions is calculated using the CFD model, and the water pressure distribution information is fitted using a multidimensional function approximation algorithm to obtain a unified mathematical expression of the water pressure load on the entire ship, which is input into the finite element model as a unit load to obtain a full-field strain result;

[0041] According to the full-field strain result, the sensor layout is optimized using an intelligent optimization algorithm to obtain the layout information of the best measuring point, wherein the layout information includes the best measuring point position and the best measuring point direction;

[0042] The influence coefficient matrix is ​​constructed using the optimized layout information of the sensors.

[0043] In some embodiments, the use of an intelligent optimization algorithm to optimize the sensor layout to obtain the layout information of the best measurement points includes:

[0044] The full-field strain results are analyzed and processed using a sensor layout optimization model based on a convolutional neural network to obtain a number of target layout areas and corresponding optimal measuring point directions, and a first number of the optimal measuring point positions are selected in each of the target layout areas; wherein the target layout area refers to an area on the outer surface of the hull of the target ship that is sensitive to the structural response;

[0045] The sensor layout optimization model also outputs a number of predicted non-target deployment areas and corresponding optimal measurement point directions, and selects a second number of the optimal measurement point positions in each of the non-target deployment areas; wherein the non-target deployment areas are located within a preset distance around the target deployment area.

[0046] The present invention also discloses an electronic device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the computer program code implements the method described in any of the preceding items when executed.

[0047] The present invention also discloses a computer storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program code is executed, the method described in any of the preceding items is implemented.

[0048] The present invention also discloses a computer program product. The computer program product is prepackaged with computer program codes. When the computer program codes are executed, the method described in any of the above items is implemented.

[0049] The beneficial effect of the present invention is that: based on the load identification algorithm, the present invention integrates fluid simulation, structural simulation and physical measurement technology to form a complete set of indirect measurement methods for the ship's outboard water pressure load by establishing a linear mapping relationship between the outboard water pressure load and the ship's structural response data. The indirect measurement method overcomes the limitations of the direct monitoring method mentioned in the background technology and realizes real-time monitoring of the ship's outboard water pressure load. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 It is a flow chart of a method for indirectly monitoring the outboard water pressure load of a ship disclosed in an embodiment of the present invention;

[0052] Figure 2 It is another overall flow chart of a method for indirectly monitoring the outboard water pressure load of a ship disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0054] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0055] Directly measuring the outboard water pressure load, such as using pressure sensors, is theoretically feasible, but faces many challenges in practical applications. For example, the sensor needs to be installed by drilling holes in the structure, which will affect the structural strength; at the same time, for large structures such as the hull, deploying a large number of pressure sensors is not only costly, but also difficult to achieve full coverage. It can be seen that how to efficiently and accurately monitor the outboard water pressure load of the ship without damaging the structural strength of the hull is a technical problem that needs to be solved.

[0056] In response to the above technical issues, such as Figure 1 , Figure 2 As shown, an embodiment of the present invention discloses a method for indirectly monitoring the outboard water pressure load of a ship, the method comprising the following steps:

[0057] S10, establishing a finite element model for accurately describing the structural characteristics and mechanical response of the target hull, and establishing a CFD model of the target hull.

[0058] S20, calculating the outboard water pressure load distribution based on the CFD model, establishing an influence coefficient matrix according to the outboard water pressure load distribution, and establishing a relationship between the outboard water pressure load and the structural response data based on the influence coefficient matrix.

[0059] S30, receiving structural response data measured by sensors arranged at optimal measuring points on the hull, and deriving a real-time outboard water pressure load based on the structural response data and the relationship by inversion.

[0060] The present invention is based on a load identification algorithm, integrates fluid simulation, structural simulation and physical measurement technology, and forms a complete set of indirect measurement methods for the ship's outboard water pressure load by establishing a linear mapping relationship between the outboard water pressure load and the ship's structural response data. This indirect measurement method overcomes the limitations of the direct monitoring method mentioned in the background technology and realizes real-time monitoring of the ship's outboard water pressure load.

[0061] In addition, after the real-time outboard water pressure load of the target ship is obtained by inversion, the real-time outboard water pressure load can be displayed intuitively so that relevant personnel can evaluate the stress condition of the hull at any time during the navigation of the ship and improve navigation safety.

[0062] Optionally, the influence coefficient matrix is ​​as follows:

[0063]

[0064] Where C is the influence coefficient matrix, n is the number of measuring points, m is the number of unit loads, and element c is mn It represents the structural response coefficient of the nth best measuring point under the unit load m;

[0065] The relationship between the outboard water pressure load and the structural response data is as follows:

[0066] R=C·F

[0067] Wherein, R is the structural response vector measured by the sensors at each of the optimal measuring points, and F is the real-time outboard water pressure load to be inverted.

[0068] In the embodiments of the present invention, the theoretical calculation formula of the ship's outboard water pressure load is often listed separately according to the pressure component or the position of action, which is complex in form and difficult to calculate. There is no method that can uniformly express the global water pressure load using a general formula. The present invention uses a unified and simple way to achieve an approximate expression of the ship's outboard water pressure load and its distribution at any time under different environmental conditions. Based on the pressure results of the numerical water tank test, it involves the ability of different multidimensional function approximation methods to reconstruct the ship's outboard water pressure load field. Through appropriate basis functions and parameter identification methods, a unified approximate expression of the ship's outboard water pressure load based on a spatial three-dimensional approximation function is constructed.

[0069] Optionally, the obtaining of a real-time outboard water pressure load based on the structural response data and the relational expression by inversion comprises:

[0070] F=(C T C) -1 C T R

[0071] In the formula, C T is the transposed matrix of the influence coefficient matrix C, (C T C) -1 C T is the pseudo-inverse matrix.

[0072] Optionally, the method further comprises:

[0073] The water pressure distribution information of the outer surface of the hull under different sea conditions is calculated using the CFD model, and the water pressure distribution information is fitted using a multidimensional function approximation algorithm to obtain a unified mathematical expression of the water pressure load on the entire ship, which is input into the finite element model as a unit load to obtain a full-field strain result;

[0074] According to the full-field strain result, the sensor layout is optimized using an intelligent optimization algorithm to obtain the layout information of the best measuring point, wherein the layout information includes the best measuring point position and the best measuring point direction;

[0075] The influence coefficient matrix is ​​constructed using the optimized layout information of the sensors.

[0076] In an embodiment of the present invention, the present invention applies the influence coefficient method to identify the outboard water pressure load of a ship. Different from the previous method based on the division of structural load-bearing units, the above-mentioned mathematical model of the unit load function based on global distribution is established, and the uncertainty of load identification is taken into account. By studying the layout optimization of multiple types of sensors, the morbidity of the influence coefficient matrix is ​​reduced.

[0077] CFD (Computational Fluid Dynamics) is a computer simulation technology that simulates the interaction between ships and water under different sea conditions by solving basic equations of fluid dynamics, such as the Navier-Stokes equations. It can take into account multiple factors such as waves, currents, and ship motion to calculate the water pressure distribution information on the outer surface of the hull. These water pressure distribution information are discrete and distributed at various locations on the outer surface of the hull, reflecting the external water pressure conditions of the ship at different locations. For example, when a ship is sailing, the bow part will be subject to higher pressure due to the impact of the water flow, while the pressure distribution on the side and stern of the ship will be different due to the flow and vortex of the water flow. Different sea conditions include different wave heights, wavelengths, wave directions, flow velocities, flow directions, and wind conditions, all of which will affect the water pressure distribution on the outer surface of the hull. The CFD model can calculate these complex sea conditions and provide a rich data basis for subsequent analysis.

[0078] Since the water pressure distribution information obtained by CFD calculation is discrete, it is difficult to be directly used for subsequent structural analysis. The present invention uses a multidimensional function approximation algorithm (such as polynomial function approximation, spline function approximation, etc.) to fit these discrete water pressure distribution information and express it as a unified mathematical expression. This mathematical expression can continuously describe the water pressure load on the entire outer surface of the hull, forming a unified mathematical expression of the water pressure load outside the whole ship. This unified expression makes the description of the water pressure load more concise and accurate, and is convenient for subsequent use as an input parameter.

[0079] The finite element model is a numerical calculation method that divides a complex structure into multiple simple units. By inputting the unified mathematical expression of the water pressure load of the entire ship as a unit load (a total of m) into the finite element model, the mechanical response of the hull under the water pressure load is simulated, and the above-mentioned influence coefficient matrix is ​​obtained. Each unit will produce corresponding strains and stresses under the action of the water pressure load according to its material properties and geometric shape. Through finite element calculation, the full-field strain results can be obtained, that is, the strain distribution of the entire hull structure under a given water pressure load. The strain distribution can reflect the deformation degree and stress concentration area of ​​the hull structure at different positions, providing a basis for the strength and stability assessment of the ship structure.

[0080] According to the full-field strain results, the sensor layout is optimized using intelligent optimization algorithms (such as genetic algorithms, particle swarm optimization algorithms, etc.) to make the sensor layout more scientific and reasonable. The full-field strain results need to be considered in the optimization process to find the best measurement point position and direction that can most accurately reflect the key response signals of the hull structure. For example, sensors are arranged in areas where strain changes drastically, or sensors are arranged at key positions that can reflect the overall deformation trend of the structure to ensure that the mechanical response information of the hull structure under different working conditions is captured to the greatest extent with the least number of sensors. In addition, the determination of the optimal measurement point position and direction also needs to balance multiple factors such as monitoring effect and cost. For example, avoid placing sensors in areas that are insensitive to structural response, or avoid increasing costs and system complexity due to overly dense sensor layout.

[0081] The influence coefficient matrix is ​​constructed using the optimized sensor layout information. The influence coefficient matrix reflects the mapping relationship between the hull structure response data (i.e., the strain data measured by the sensor) and the real-time outboard water pressure load. Specifically, the elements in the influence coefficient matrix describe the strain changes generated at different sensor positions when the unit water pressure load changes. Through this matrix, the relationship between the strain signal measured by the sensor and the outboard water pressure load can be established, providing a mathematical basis for subsequent load inversion.

[0082] In some embodiments, the use of an intelligent optimization algorithm to optimize the sensor layout to obtain the layout information of the best measurement points includes:

[0083] The full-field strain results are analyzed and processed using a sensor layout optimization model based on a convolutional neural network to obtain a number of target layout areas and corresponding optimal measuring point directions, and a first number of the optimal measuring point positions are selected in each of the target layout areas; wherein the target layout area refers to an area on the outer surface of the hull of the target ship that is sensitive to the structural response;

[0084] The sensor layout optimization model also outputs a number of predicted non-target deployment areas and corresponding optimal measurement point directions, and selects a second number of the optimal measurement point positions in each of the non-target deployment areas; wherein the non-target deployment areas are located within a preset distance around the target deployment area.

[0085] In an embodiment of the present invention, in addition to the aforementioned intelligent optimization algorithms such as genetic algorithms and particle swarm optimization algorithms, the present invention can also use a sensor layout optimization model based on a convolutional neural network to analyze and process the full-field strain results. Convolutional neural network is a deep learning model that has outstanding performance in the fields of image recognition and data feature extraction. The present invention regards the full-field strain results as a "data image", which contains the strain information of the hull structure at different positions. Through its convolutional layer, pooling layer and fully connected layer, CNN can automatically extract complex features in the full-field strain results, including gradient changes in strain, local strain concentration areas, strain distribution patterns, etc., which helps to find areas that are sensitive to structural response, namely target layout areas, and non-target layout areas that are insensitive to structural response and are located within a preset distance around the target layout area.

[0086] The above-mentioned target deployment area refers to the area on the outer surface of the hull of the target ship that is sensitive to structural response, which is more susceptible to the external water pressure load and may be a high-risk area for structural failure. For example, the bow, stern, near the keel, structural joints and other parts of the ship are usually areas sensitive to structural response due to their special structure and stress conditions. Through the analysis of the full-field strain results by CNN, these areas sensitive to structural response can be automatically identified. The model can divide the outer surface of the hull into different areas based on factors such as the concentration of strain, the severity of strain changes, and the distribution pattern of strain, and determine which areas are target deployment areas.

[0087] For each target layout area, the sensor layout optimization model also outputs the corresponding optimal measurement point direction. The determination of the optimal measurement point direction takes into account the force direction and strain direction of the structure in the area. For example, in the part of the structure that bears longitudinal tension, the optimal measurement point direction of the sensor may be arranged along the force direction to most effectively capture the strain signal. This helps to improve the accuracy and sensitivity of sensor measurements and ensure that the most critical structural response information in the area can be monitored.

[0088] After the target deployment area is determined, a first number of optimal measurement point positions will be selected in each target deployment area. This number can be determined based on actual conditions. For example, if the structural importance of the target deployment area is higher, more sensors will be set therein to ensure effective monitoring of key parts and timely detection of possible structural damage or failure risks. The optimal measurement point directions of the optimal measurement point positions in each target deployment area are consistent.

[0089] The above-mentioned full-field strain results may be abnormally high or low in some parts, for example, when the water pressure distribution information calculated by the aforementioned CFD model is locally inaccurate. Therefore, in addition to the target layout area, the sensor layout optimization model of the present invention will also output a number of predicted non-target layout areas and the corresponding optimal measurement point directions. At the same time, the non-target layout area is an area not far from the target layout area, that is, within a preset distance. In this way, the structural response data measured by the sensors in the adjacent area can be used to analyze and obtain a more accurate real-time outboard water pressure load. Among them, the second number in the non-target layout area should be less than the first number in the target layout area, for example, the first number is 6-10, and the second number is 2-5.

[0090] The above-mentioned sensor layout optimization model may include two sub-models, one of which is used to analyze and process the full-field strain results to obtain a number of target layout areas and corresponding optimal measurement point directions, and the other sub-model is used to analyze and process the full-field strain results to obtain a number of non-target layout areas and corresponding optimal measurement point directions. For the specific internal structure and training process of the sensor layout optimization model, the existing method can be adopted, and the present invention will not be repeated here.

[0091] The embodiment of the present invention further discloses an indirect monitoring system for outboard water pressure load of a ship, the system comprising a plurality of sensors, a processor and a memory; the processor calls a computer program code in the memory to execute the following steps:

[0092] Establish a finite element model for accurately describing the structural characteristics and mechanical response of the target ship, and establish a CFD model of the target ship;

[0093] Calculating the outboard water pressure load distribution based on the CFD model, establishing an influence coefficient matrix according to the outboard water pressure load distribution, and establishing a relationship between the outboard water pressure load and the structural response data based on the influence coefficient matrix;

[0094] Structural response data measured by sensors arranged at optimal measuring points on the hull are received, and real-time outboard water pressure load is obtained by inversion based on the structural response data and the relationship.

[0095] An embodiment of the present invention further discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the computer program code implements the method described in any of the preceding items when executed.

[0096] The embodiment of the present invention further discloses a computer storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program code is executed, the method as described in any of the preceding items is implemented.

[0097] The embodiment of the present invention further discloses a computer program product. The computer program product is prepackaged with computer program codes. When the computer program codes are executed, the method described in any of the above items is implemented.

[0098] The device embodiments described above are merely illustrative, wherein the designed modules may or may not be physically separated, i.e., may be located in one place, or may be distributed to multiple locations. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. Those of ordinary skill in the art may understand and implement the present invention without creative effort.

[0099] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0100] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for indirect monitoring of outboard water pressure load of a ship, characterized in that: The method comprises the following steps: Establish a finite element model for accurately describing the structural characteristics and mechanical response of the target hull, and establish a CFD model of the target hull; Calculating the outboard water pressure load distribution based on the CFD model, establishing an influence coefficient matrix according to the outboard water pressure load distribution, and establishing a relationship between the outboard water pressure load and the structural response data based on the influence coefficient matrix; The structural response data measured by sensors arranged at the best measuring points on the hull are received, and the real-time outboard water pressure load is obtained by inversion based on the structural response data and the relationship.

2. A method for indirect monitoring of outboard water pressure load of a ship according to claim 1, characterized in that: The influence coefficient matrix is ​​as follows: Where C is the influence coefficient matrix, n is the number of measuring points, m is the number of unit loads, and element c is mn It represents the structural response coefficient of the nth best measuring point under the unit load m; The relationship between the outboard water pressure load and the structural response data is as follows: R=C·F Wherein, R is the structural response vector measured by the sensors at each of the optimal measuring points, and F is the real-time outboard water pressure load to be inverted.

3. A method for indirect monitoring of outboard water pressure load of a ship according to claim 2, characterized in that: The real-time outboard water pressure load is obtained based on the structural response data and the relational expression, including: F=(C T C) -1 C T R In the formula, C T is the transposed matrix of the influence coefficient matrix C, (C T C) -1 C T is the pseudo-inverse matrix.

4. A method for indirect monitoring of outboard water pressure load of a ship according to claim 3, characterized in that: The method further comprises: The water pressure distribution information of the outer surface of the hull under different sea conditions is calculated using the CFD model, and the water pressure distribution information is fitted using a multidimensional function approximation algorithm to obtain a unified mathematical expression of the water pressure load on the entire ship, which is input into the finite element model as a unit load to obtain a full-field strain result; According to the full-field strain result, the sensor layout is optimized using an intelligent optimization algorithm to obtain the layout information of the best measuring point, wherein the layout information includes the best measuring point position and the best measuring point direction; The influence coefficient matrix is ​​constructed using the optimized layout information of the sensors.

5. A method for indirect monitoring of outboard water pressure load of a ship according to claim 4, characterized in that: Use intelligent optimization algorithms to optimize sensor layout and obtain the best measurement point layout information, including: The full-field strain results are analyzed and processed using a sensor layout optimization model based on a convolutional neural network to obtain a number of target layout areas and corresponding optimal measuring point directions, and a first number of the optimal measuring point positions are selected in each of the target layout areas; wherein the target layout area refers to an area on the outer surface of the hull of the target ship that is sensitive to the structural response; The sensor layout optimization model also outputs a number of predicted non-target deployment areas and corresponding optimal measurement point directions, and selects a second number of the optimal measurement point positions in each of the non-target deployment areas; wherein the non-target deployment areas are located within a preset distance around the target deployment area.

6. A system for indirectly monitoring the outboard water pressure load of a ship, the system comprising a plurality of sensors, a processor and a memory; characterized in that: The processor calls the computer program code in the memory to perform the following steps: Establish a finite element model for accurately describing the structural characteristics and mechanical response of the target hull, and establish a CFD model of the target hull; Calculating the outboard water pressure load distribution based on the CFD model, establishing an influence coefficient matrix according to the outboard water pressure load distribution, and establishing a relationship between the outboard water pressure load and the structural response data based on the influence coefficient matrix; The structural response data measured by sensors arranged at the best measuring points on the hull are received, and the real-time outboard water pressure load is obtained by inversion based on the structural response data and the relationship.

7. The indirect monitoring system for outboard water pressure load of a ship according to claim 6, characterized in that: Also includes: The water pressure distribution information of the outer surface of the hull under different sea conditions is calculated using the CFD model, and the water pressure distribution information is fitted using a multidimensional function approximation algorithm to obtain a unified mathematical expression of the water pressure load on the entire ship, which is input into the finite element model as a unit load to obtain a full-field strain result; According to the full-field strain result, the sensor layout is optimized using an intelligent optimization algorithm to obtain the layout information of the best measuring point, wherein the layout information includes the best measuring point position and the best measuring point direction; The influence coefficient matrix is ​​constructed using the optimized layout information of the sensors.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the computer program code implements the method according to any one of claims 1 to 5 when executed.

9. A computer storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program code is executed, the method according to any one of claims 1 to 5 is implemented.

10. A computer program product, characterized in that: The computer program product comprises a computer program code, and when the computer program code is executed, the method according to any one of claims 1 to 5 is implemented.

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