Intelligent detection method and system for underwater engineering structure based on digital twinning

Abstract

This invention discloses an intelligent detection method and system for underwater engineering structures based on digital twins. The method includes: establishing a finite element master model based on the design scheme and actual working conditions of the underwater engineering structure; evaluating and issuing early warnings for the underwater engineering structure based on the finite element master model; if the evaluated structural performance fails to meet the standards, issuing an alarm message and proceeding to the maintenance step; if the structural performance meets the standards, generating a detection point matrix based on the evaluation results; performing flow field detection and structural detection on the underwater engineering structure based on the detection point matrix to obtain a detection dataset; updating the finite element master model based on the detection dataset and re-evaluating and issuing early warnings for the underwater engineering structure. This invention proposes a method for establishing a digital twin of an underwater engineering structure, using an unmanned underwater vehicle for flow field data acquisition and non-destructive testing of the structure, constructing a digital twin system with the finite element master model as its core, and realizing the monitoring, evaluation, and early warning of underwater structural performance.

Description

Technical Field

[0001] This invention relates to the field of underwater detection technology, and in particular to an intelligent detection method and system for underwater engineering structures based on digital twins. Background Technology

[0002] The statements in this section merely refer to the background art related to this invention and do not necessarily constitute prior art.

[0003] Underwater engineering structures are widely used in inland waterways and oceans. Due to the complex working environment, the increasingly large and complex underwater engineering structures are not only costly to construct but also difficult to monitor and maintain. Therefore, accurate detection and evaluation of their performance are particularly important. By conducting health checks and damage diagnoses on the structures, early warnings of potential damage can be provided, allowing for timely repairs and reinforcement, thereby avoiding potential economic losses and casualties.

[0004] Conventional monitoring methods often involve deploying sensors on the surface of a structure. However, once deployed, these sensors cannot be moved, making it difficult to track and monitor performance changes that occur during the structure's operation.

[0005] Unmanned underwater vehicles (UUVs) can be used for comprehensive inspection of underwater engineering structures, as well as for targeted inspections of specific areas such as welds. However, the data obtained cannot be directly used for structural performance evaluation and damage diagnosis. Mathematical models built using conventional statistical or machine learning methods lack the support of mechanical principles, making it difficult to accurately reproduce changes in structural performance; their accuracy and interpretability are both insufficient. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides an intelligent detection method and system for underwater engineering structures based on digital twins. This invention proposes a method for establishing a digital twin of an underwater engineering structure, which uses an unmanned underwater vehicle to collect flow field data and perform non-destructive testing of the structure. A digital twin system with a finite element master model as its core is constructed to achieve monitoring, evaluation, and early warning of the underwater structure's performance.

[0007] In a first aspect, the present invention provides an intelligent detection method for underwater engineering structures based on digital twins;

[0008] Intelligent detection methods for underwater engineering structures based on digital twins include:

[0009] Based on the design scheme and actual working conditions of the underwater engineering structure, a finite element master model is established.

[0010] Based on the finite element master model, underwater engineering structures are evaluated and warned. If the evaluated structural performance does not meet the standards, an alarm message is issued and the process jumps to the maintenance step; if the structural performance meets the standards, a detection point matrix is ​​generated based on the evaluation results.

[0011] Based on the detection point matrix, flow field detection and structural detection of underwater engineering structures are performed to obtain a detection dataset.

[0012] Based on the detection dataset, the finite element master model is updated, and the underwater engineering structure is re-evaluated and given an early warning.

[0013] Furthermore, the intelligent detection method for underwater engineering structures based on digital twins also includes:

[0014] Receive several alternative repair solutions submitted in response to alarm information;

[0015] Based on each alternative maintenance scheme, a finite element sub-model is generated on the basis of the finite element master model; similarly, several finite element sub-models are obtained.

[0016] All finite element pair models are calculated and compared to select the optimal finite element pair model; underwater engineering structures are then repaired according to the optimal finite element pair model.

[0017] After the repair is completed, the optimal finite element sub-model is used to replace the finite element master model, and the process jumps to S102 to continue execution.

[0018] Secondly, this invention provides an intelligent detection device for underwater engineering structures based on digital twins;

[0019] A digital twin-based intelligent inspection device for underwater engineering structures includes:

[0020] The model building module is configured to: build a finite element master model based on the design scheme and actual working conditions of the underwater engineering structure;

[0021] The assessment and early warning module is configured to: assess and issue early warnings for underwater engineering structures based on the finite element master model; if the assessed structural performance fails to meet the standards, an alarm message is issued and the process is redirected to the maintenance step; if the structural performance meets the standards, a detection point matrix is ​​generated based on the assessment results.

[0022] The detection module is configured to perform flow field detection and structural detection of underwater engineering structures based on the detection point array, and obtain a detection dataset;

[0023] The update module is configured to update the finite element master model based on the detection dataset and return it to the evaluation and early warning module.

[0024] Furthermore, the intelligent detection device for underwater engineering structures based on digital twins also includes:

[0025] The receiving module is configured to receive several alternative maintenance solutions submitted in response to alarm information.

[0026] The sub-model generation module is configured to generate a finite element sub-model based on the finite element master model for each alternative maintenance scheme; similarly, several finite element sub-models are obtained.

[0027] The calculation and comparison module is configured to: perform calculations and comparisons on all finite element pair models, select the optimal finite element pair model, and perform repairs on underwater engineering structures according to the optimal finite element pair model;

[0028] The replacement module is configured to: after maintenance is completed, replace the finite element master model with the optimal finite element sub-model, and then jump to the evaluation and early warning module to continue execution.

[0029] Thirdly, the present invention also provides an electronic device, comprising:

[0030] Memory, used for non-transitory storage of computer-readable instructions; and

[0031] Processor, for executing the computer-readable instructions,

[0032] When the computer-readable instructions are executed by the processor, they perform the method described in the first aspect above.

[0033] Fourthly, the present invention also provides a storage medium for non-transitory storage of computer-readable instructions, wherein, when the non-transitory computer-readable instructions are executed by a computer, the instructions for the method described in the first aspect are executed.

[0034] Fifthly, the present invention also provides an intelligent detection system for underwater engineering structures based on digital twins, comprising: an unmanned underwater vehicle and a server;

[0035] The server includes: a hardware computing platform, on which a software environment is mounted;

[0036] The unmanned underwater vehicle collects data and stores it on a hardware computing platform to build digital models of underwater engineering structures.

[0037] The hardware computing platform is used for storing the collected data and deploying the software environment, providing basic resources for the establishment of digital models of underwater engineering structures.

[0038] The software environment is deployed on a hardware computing platform for building digital models of underwater engineering structures. It includes finite element software, CFD software, mathematical software, machine learning algorithm sets, heterogeneous databases, and basic mathematical libraries that support the above software.

[0039] In a sixth aspect, the present invention also provides a computer program product, including a computer program that, when run on one or more processors, is used to implement the method described in the first aspect above.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] (1) Based on the real working environment of underwater engineering structures, a digital model supported by mechanical principles was constructed.

[0042] (2) By collecting flow field data through unmanned underwater vehicles, the loads on the working environment of underwater engineering structures, such as water flow, waves, and tides, can be accurately reproduced.

[0043] (3) Use unmanned underwater vehicles to conduct non-destructive testing on underwater engineering structures to achieve accurate perception of the structural status.

[0044] (4) A mechanical model of the underwater engineering structure was established based on the finite element method. The comprehensive evaluation of the structural performance was achieved through static calibration, dynamic damage assessment, fatigue durability analysis, etc. The evaluation results were used for monitoring and early warning.

[0045] (5) For underwater engineering structures that need repair, the repair scheme is evaluated by finite element model, the feasibility of the scheme is verified, and the repair schemes are compared.

[0046] (6) This invention improves the accuracy of performance evaluation and failure early warning for underwater engineering structures, thereby better avoiding economic losses and casualties that may result from structural failure. First, the data collected by the unmanned underwater vehicle is more comprehensive and accurate, enabling a more complete reconstruction of the environmental loads on the structure and the damage during its service life. Second, the digital model established based on mechanical principles ensures the accuracy of the evaluation results from a mechanistic perspective.

[0047] This invention provides data support for maintenance decisions by comparing maintenance schemes for underwater engineering structures, thereby helping to save decision-making time, improve maintenance quality, and extend the life of the structure. Attached Figure Description

[0048] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0049] Figure 1 System functional module diagram;

[0050] Figure 2 This is a flowchart of the method. Detailed Implementation

[0051] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0052] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0053] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0054] All data acquisition in this embodiment is carried out in accordance with laws and regulations and with user consent, and the data is used legally.

[0055] Terminology Explanation:

[0056] Unmanned underwater vehicle: An unmanned underwater vehicle, mainly used for underwater exploration.

[0057] Underwater engineering structures: the underwater parts of large-scale water conservancy or marine engineering structures such as dams, bridges, and marine engineering equipment.

[0058] Digital twin system: For physical entities, based on measured data, a digital mapping is constructed through mathematical modeling. Through the interaction between the physical world and the digital world, the physical object can be monitored, analyzed and optimized.

[0059] Example 1

[0060] This embodiment provides an intelligent detection method for underwater engineering structures based on digital twins;

[0061] like Figure 1 and Figure 2 As shown, the intelligent detection method for underwater engineering structures based on digital twins includes:

[0062] S101: Establish a finite element master model based on the design scheme and actual working conditions of the underwater engineering structure;

[0063] S102: Based on the finite element master model, the underwater engineering structure is evaluated and an early warning is issued. If the evaluated structural performance does not meet the standards, an alarm message is issued and the process jumps to the maintenance step; if the structural performance meets the standards, a detection point matrix is ​​generated based on the evaluation results.

[0064] S103: Based on the detection point matrix, perform flow field detection and structural detection of underwater engineering structures to obtain the detection dataset;

[0065] S104: Update the finite element master model based on the detection dataset and return to S102.

[0066] Furthermore, the finite element master model includes: the finite element mesh of each component, the connection relationship between the components, the boundary conditions (loads and constraints) of the structure, the material properties (elastic and plastic) of each component, the analysis type (static and dynamic), and the analysis parameters.

[0067] Furthermore, the underwater engineering structure is evaluated and warned based on the finite element master model; the evaluation and warning methods used include: static calibration, dynamic damage assessment and fatigue durability analysis.

[0068] Furthermore, the detection point array includes: flow field detection point coordinates, flow field detection type, structure detection point coordinates, and structure detection point type.

[0069] Furthermore, after step S102, the method further includes: densifying the detection array in the structurally weak areas identified in the evaluation.

[0070] For example, the intensive processing means that the four points above, below, left, and right of the weak point are also regarded as points to be detected.

[0071] Furthermore, the detection dataset of S103 includes: a flow field dataset and a structure dataset; wherein, the flow field dataset includes: flow velocity and pressure; and the structure dataset includes: structural deformation and damage.

[0072] Furthermore, the flow field detection and structural detection of the underwater engineering structure based on the detection point array in S103 are performed by an unmanned underwater vehicle.

[0073] Further, S104: updating the finite element master model based on the detection dataset; specifically including:

[0074] S1041: Based on the flow field dataset, establish a fluid dynamics model and calculate the force exerted by the water flow on the underwater engineering structure; based on the force, update the load boundary conditions in the finite element master model;

[0075] S1042: Update the component meshes and the connection relationships between components in the finite element master model based on the structure dataset.

[0076] Furthermore, S104: updating the finite element master model based on the detection dataset; also includes:

[0077] S1043: For cracks in underwater engineering structures, model the cracks and describe the local mechanical behavior of the structure.

[0078] Furthermore, the intelligent detection method for underwater engineering structures based on digital twins also includes:

[0079] S105: Receive several alternative maintenance solutions submitted in response to alarm information;

[0080] S106: Based on each alternative maintenance scheme, generate a finite element sub-model on the basis of the finite element master model; similarly, obtain several finite element sub-models.

[0081] S107: Compare and calculate all finite element pair models to select the optimal finite element pair model; perform underwater engineering structure repairs according to the optimal finite element pair model.

[0082] S108: After the repair is completed, replace the finite element master model with the optimal finite element sub-model, and jump to S102 to continue execution.

[0083] Example 2

[0084] This embodiment provides an intelligent detection device for underwater engineering structures based on digital twins;

[0085] A digital twin-based intelligent inspection device for underwater engineering structures includes:

[0086] The model building module is configured to: build a finite element master model based on the design scheme and actual working conditions of the underwater engineering structure;

[0087] The assessment and early warning module is configured to: assess and issue early warnings for underwater engineering structures based on the finite element master model; if the assessed structural performance fails to meet the standards, an alarm message is issued and the process is redirected to the maintenance steps; if the structural performance meets the standards, a detection point matrix is ​​generated based on the assessment results.

[0088] The detection module is configured to perform flow field detection and structural detection of underwater engineering structures based on the detection point array, and obtain a detection dataset;

[0089] The update module is configured to update the finite element master model based on the detection dataset and return it to the evaluation and early warning module.

[0090] Furthermore, the intelligent detection device for underwater engineering structures based on digital twins also includes:

[0091] The receiving module is configured to receive several alternative maintenance solutions submitted in response to alarm information.

[0092] The sub-model generation module is configured to generate a finite element sub-model based on the finite element master model for each alternative maintenance scheme; similarly, several finite element sub-models are obtained.

[0093] The calculation and comparison module is configured to: perform calculations and comparisons on all finite element pair models, select the optimal finite element pair model, and perform repairs on underwater engineering structures according to the optimal finite element pair model;

[0094] The replacement module is configured to: after maintenance is completed, replace the finite element master model with the optimal finite element sub-model, and then jump to the evaluation and early warning module to continue execution.

[0095] Example 3

[0096] This embodiment also provides an electronic device, including: one or more processors, one or more memories, and one or more computer programs; wherein, the processor is connected to the memory, and the one or more computer programs are stored in the memory. When the electronic device is running, the processor executes the one or more computer programs stored in the memory to cause the electronic device to perform the method described in Embodiment 1.

[0097] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0098] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0099] In the implementation process, each step of the above method can be completed by the integrated logic circuits in the processor hardware or by software instructions.

[0100] The method in Embodiment 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0101] Those skilled in the art will recognize that the units and algorithm steps described in connection with the various examples of this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0102] Example 4

[0103] This embodiment also provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, complete the method described in Embodiment 1.

[0104] Example 5

[0105] This embodiment also provides an intelligent detection system for underwater engineering structures based on digital twins;

[0106] The system mainly consists of two parts: the digital world and the physical world. The physical world primarily includes the unmanned underwater vehicle and the hardware computing platform; the digital world mainly includes digital models of underwater engineering structures and the high-performance software environment used to build these models. The system architecture diagram is shown below. Figure 1 As shown.

[0107] A digital twin-based intelligent inspection system for underwater engineering structures includes: an unmanned underwater vehicle and a server;

[0108] The server includes: a hardware computing platform, on which a software environment is mounted;

[0109] The unmanned underwater vehicle collects data and stores it on a hardware computing platform to build digital models of underwater engineering structures.

[0110] The hardware computing platform is used for storing the collected data and deploying the software environment, providing basic resources for the establishment of digital models of underwater engineering structures.

[0111] The software environment is deployed on a hardware computing platform for building digital models of underwater engineering structures. It includes finite element software, CFD software, mathematical software, machine learning algorithm sets, heterogeneous databases, and basic mathematical libraries that support the above software.

[0112] Furthermore, the finite element software is used to construct a finite element model of an underwater engineering structure; the finite element model includes a finite element master model and a finite element copy model.

[0113] CFD (Computational Fluid Dynamics) software is used to construct fluid dynamic models of the flow field in the waters near underwater engineering structures.

[0114] A set of mathematical software and machine learning algorithms for building early warning assessment models for underwater engineering structures.

[0115] Heterogeneous databases are used to store monitoring datasets collected by unmanned underwater vehicles, the coordinates of detection points output by evaluation and early warning models, and result file sets generated by each model.

[0116] The coordinates of the detection points are transmitted to the unmanned underwater vehicle, enabling it to perform detection according to the coordinates.

[0117] Furthermore, the digital model is a mapping of the underwater engineering structure in the digital world, including finite element model, fluid dynamics model, assessment and early warning model, and related data.

[0118] The finite element model includes: the finite element master model and the finite element copy model.

[0119] The finite element master model is used to analyze the mechanical properties of underwater engineering structures using the finite element method.

[0120] The finite element replica model is a small-scale modification of the finite element master model, mainly used for mechanical analysis of underwater engineering structures altered due to maintenance.

[0121] The fluid dynamics model is used to analyze the flow field in the waters near underwater engineering structures, thereby providing accurate load inputs for the finite element model.

[0122] The assessment and early warning model is based on finite element analysis and uses statistical principles or machine learning techniques to establish criteria for assessing damage and safety of underwater engineering structures, thereby providing early warnings for their maintenance.

[0123] Furthermore, the unmanned underwater vehicle is used for the detection of underwater engineering structures and nearby waters.

[0124] The underwater detection equipment carried by the unmanned underwater vehicle includes: structural detection equipment and flow field detection equipment.

[0125] Among them, structural testing equipment includes: ultrasonic testing equipment, AC electromagnetic field testing equipment, electric field characteristic testing equipment, and underwater imaging testing equipment; structural testing equipment is used for non-destructive testing of underwater engineering structures.

[0126] Among them, the flow field detection equipment includes: pressure sensors and flow velocity sensors. The flow field detection equipment is used to detect the flow field in the waters near underwater engineering structures.

[0127] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A digital twin-based intelligent detection method for underwater engineering structures, characterized by: include: Based on the design scheme and actual working conditions of the underwater engineering structure, a finite element master model is established. The finite element master model includes: the finite element mesh of each component, the connection relationship between the components, the boundary conditions of the structure, the material properties of each component, the analysis type and analysis parameters; Based on the finite element master model, underwater engineering structures are evaluated and warned. If the evaluated structural performance does not meet the standards, an alarm message is issued and the process jumps to the maintenance step; if the structural performance meets the standards, a detection point matrix is ​​generated based on the evaluation results. Based on the detection point matrix, flow field detection and structural detection of underwater engineering structures are performed to obtain a detection dataset; the detection point matrix includes: flow field detection point coordinates, flow field detection type, structural detection point coordinates, and structural detection point type; The detection dataset includes: a flow field dataset and a structure dataset; wherein, the flow field dataset includes: flow velocity and pressure; and the structure dataset includes: structural deformation and damage. The flow field and structural inspection of underwater engineering structures are carried out using unmanned underwater vehicles. Based on the detection dataset, the finite element master model is updated, and the underwater engineering structure is re-evaluated and warned. The updating of the finite element master model based on the detection dataset specifically includes: Based on the flow field dataset, a fluid dynamics model was established to calculate the force exerted by the water flow on the underwater engineering structure; based on the force, the load boundary conditions in the finite element master model were updated. Based on the structural dataset, update the component meshes and the connection relationships between components in the finite element master model.

2. The intelligent detection method for underwater engineering structures based on digital twins as described in claim 1, characterized in that, The method further includes: Receive several alternative repair solutions submitted in response to alarm information; Based on each alternative maintenance scheme, a finite element sub-model is generated on the basis of the finite element master model; similarly, several finite element sub-models are obtained. All finite element pair models are calculated and compared to select the optimal finite element pair model; underwater engineering structures are then repaired according to the optimal finite element pair model. After the repair is completed, the optimal finite element sub-model is used to replace the finite element master model, and the underwater engineering structure is re-evaluated and an early warning is issued.

3. The intelligent detection method for underwater engineering structures based on digital twins as described in claim 1, characterized in that, Based on the finite element master model, underwater engineering structures are evaluated and given early warning. The assessment and early warning methods used include: static calibration, dynamic damage assessment, and fatigue durability analysis.

4. An intelligent detection device for underwater engineering structures based on digital twins, characterized in that, include: The model building module is configured to: build a finite element master model based on the design scheme and actual working conditions of the underwater engineering structure; The finite element master model includes: the finite element mesh of each component, the connection relationship between the components, the boundary conditions of the structure, the material properties of each component, the analysis type and analysis parameters; The assessment and early warning module is configured to: assess and issue early warnings for underwater engineering structures based on a finite element master model; if the assessed structural performance fails to meet standards, an alarm message is issued, and the process proceeds to the maintenance step; if the structural performance meets standards, a detection point matrix is ​​generated based on the assessment results; the detection point matrix includes: flow field detection point coordinates, flow field detection type, structural detection point coordinates, and structural detection point type; the detection module is configured to: perform flow field detection and structural detection of the underwater engineering structure based on the detection point matrix, obtaining a detection dataset; the detection dataset includes: a flow field dataset and a structural dataset; wherein, the flow field dataset includes: flow velocity and pressure; the structural dataset includes: structural deformation and damage; The flow field and structural inspection of underwater engineering structures are carried out using unmanned underwater vehicles. The update module is configured to: update the finite element master model based on the detection dataset and return the result to the evaluation and early warning module; the update of the finite element master model based on the detection dataset specifically includes: Based on the flow field dataset, a fluid dynamics model was established to calculate the force exerted by the water flow on the underwater engineering structure; based on the force, the load boundary conditions in the finite element master model were updated. Based on the structural dataset, update the component meshes and the connection relationships between components in the finite element master model.

5. The intelligent detection device for underwater engineering structures based on digital twins as described in claim 4, characterized in that, The detection device also includes: The receiving module is configured to receive several alternative maintenance solutions submitted in response to alarm information. The sub-model generation module is configured to generate a finite element sub-model based on the finite element master model for each alternative maintenance scheme; similarly, several finite element sub-models are obtained. The calculation and comparison module is configured to: perform calculations and comparisons on all finite element pair models, select the optimal finite element pair model, and perform repairs on underwater engineering structures according to the optimal finite element pair model; The replacement module is configured to: after maintenance is completed, replace the finite element master model with the optimal finite element sub-model, and then jump to the evaluation and early warning module to continue execution.

6. An electronic device, characterized in that it comprises: Memory is used to store computer-readable instructions in a non-transitory manner. as well as Processor, for executing the computer-readable instructions, When the computer-readable instructions are executed by the processor, they perform the method according to any one of claims 1-3.

7. A storage medium characterized in that it non-transitory stores computer-readable instructions, wherein, When the non-transitory computer-readable instructions are executed by a computer, the instructions of the method according to any one of claims 1-3 are executed.

8. An intelligent detection system for underwater engineering structures based on digital twins, employing the intelligent detection method for underwater engineering structures based on digital twins as described in any one of claims 1-3, characterized in that, include: Unmanned underwater vehicles and servers; The server includes: a hardware computing platform, on which a software environment is mounted; The unmanned underwater vehicle collects data and stores it on a hardware computing platform to build digital models of underwater engineering structures. The hardware computing platform is used for storing the collected data and deploying the software environment, providing basic resources for the establishment of digital models of underwater engineering structures. The software environment is deployed on a hardware computing platform for building digital models of underwater engineering structures. It includes finite element software, CFD software, mathematical software, machine learning algorithm sets, heterogeneous databases, and basic mathematical libraries that support the above software.

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