Ship test and maintenance process digital twinborn body construction method

Abstract

The invention discloses a method for constructing a digital twinborn body in a ship test and maintenance process, which comprises the following steps of: constructing a multi-dimensional digital twinborn body: integrating a geometric model, physical characteristics, operation behaviors, maintenance rules and connection interaction data of a ship, and constructing a ship multi-dimensional digital twinborn model, the performance and behaviors of the ship under different environment conditions are simulated; a sensing device is deployed to monitor key performance indexes of the ship in real time, and real-time data are transmitted through a wired or wireless network; a virtual-real connection interaction mechanism is constructed; real-time data exchange between a ship physical entity and a digital twin is realized through an OPC UA server, and message transmission is realized through an MQTT protocol; and providing intelligent decision support: generating maintenance suggestions and decision support information based on real-time data and the digital twins in combination with historical data and an expert knowledge base. According to the invention, real-time monitoring and intelligent decision support of the whole ship test and maintenance process are realized.

Description

Technical Field

[0001] This invention relates to the field of marine engineering, and more specifically to a method for constructing a digital twin of a ship testing and maintenance process. Background Technology

[0002] With the rapid development of global trade and the maritime economy, ships, as a major means of transportation, have received widespread attention for their safety, reliability, and economy. Ship testing and maintenance are crucial for ensuring their performance and extending their service life, affecting not only navigational safety but also transportation efficiency and operating costs. Traditional ship testing and maintenance primarily rely on periodic manual inspections and experience-based maintenance strategies. However, with changes in technology and the operating environment, their limitations have become increasingly apparent, mainly as follows: (1) Insufficient real-time capability: Traditional periodic inspections cannot achieve real-time monitoring of the ship's status, resulting in delays in the discovery and handling of potential problems. This time delay not only increases the safety risks of navigation, but may also cause serious economic losses at critical moments.

[0003] (2) Low accuracy: Experience-based maintenance decisions often lack accuracy and may fail to accurately assess the actual condition of the vessel, thus making it impossible to formulate an optimal maintenance plan and limiting the optimization space of the maintenance plan. The actual condition of the vessel is affected by a variety of factors, and relying solely on experience to make judgments may lead to unreasonable maintenance plans and fail to achieve the best allocation of resources.

[0004] (3) Inefficient: Traditional maintenance processes are often time-consuming and costly, especially when parts need to be replaced or large-scale repairs are required, which may lead to extended downtime and increased economic losses.

[0005] (4) Insufficient data utilization: A large amount of data is generated during the existing ship testing and maintenance process, but the potential value of this data is often not fully explored and utilized. The lack of in-depth analysis and mining of the data makes maintenance decisions lack strong data support, which limits the space for optimization of maintenance strategies and thus affects the overall operating efficiency of the ship.

[0006] (5) Poor environmental adaptability: Ships operate in different marine environments, and their performance is affected by many factors. Traditional methods are difficult to adapt to the changing environmental conditions and the impact assessment on ship performance is not comprehensive enough.

[0007] Given the numerous problems with traditional ship testing and maintenance technologies, this invention proposes a method for simulating and optimizing the ship testing and maintenance process based on digital twin technology. Summary of the Invention

[0008] To address the shortcomings of traditional ship testing and maintenance methods, this invention provides a method for constructing a digital twin of the ship testing and maintenance process. This method can accurately simulate the behavior of ships under various testing and maintenance scenarios, providing a powerful decision support tool for ship maintenance and ensuring the efficient and safe operation of ships.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is as follows: The first aspect of the present invention provides a method for constructing a digital twin of a ship testing and maintenance process, the method comprising: (1) Constructing a multi-dimensional digital twin: Integrating the ship's geometric model, physical characteristics, operational behavior, maintenance rules, and connection interaction data to construct a multi-dimensional digital twin model of the ship, so as to simulate the ship's performance and behavior under different environmental conditions; wherein, the multi-dimensional digital twin includes geometric dimension, physical dimension, behavioral dimension, rule dimension, and connection interaction dimension; the connection interaction dimension is used to realize parameter linkage and state synchronization between different dimension models; (2) Establish a data acquisition framework: Deploy sensing devices to monitor the key performance indicators of the ship in real time and transmit real-time data through wired or wireless networks; (3) Construct a virtual-physical connection and interaction mechanism: Real-time data exchange between the physical entity of the ship and the digital twin is realized through the OPC UA server, and message transmission is realized through the MQTT protocol; (4) Provide intelligent decision support: Based on real-time data and digital twins, combined with historical data and expert knowledge base, generate maintenance suggestions and decision support information.

[0010] In the above scheme, constructing a multi-dimensional digital twin includes: The process involves acquiring point cloud data of the ship, denoising and simplifying it, and then importing it into CAD or SolidWorks software to build a high-precision 3D model. This model is then imported into the Unity engine to utilize mesh optimization tools to repair the model structure. For movable parts, the model joints are bound in Unity using skeletal animation, keyframe animations are set to simulate motion trajectories, and collision body components are assigned using the physics engine to achieve spatial interference detection between parts. Unity's C# scripting system is used to correlate real-time data to adjust the model. Based on the geometric model, material properties and environmental interaction characteristics are assigned to simulate the physical behavior of the equipment.

[0011] In the above scheme, the data acquisition framework monitors the ship's key performance indicators in real time and automatically adjusts maintenance strategies based on the monitoring results to optimize the ship's operational efficiency and maintenance plans, including: The perception layer captures real-time device operating status data based on sensors; The transport layer, including the edge gateway, is used to convert sensor data into OPC UA variable nodes or MQTT messages according to its real-time requirements and data frequency, and select the appropriate local industrial network or remote wireless network for transmission. The decision-making layer analyzes data through a stream processing engine, combines a rule base with machine learning to determine the state, and generates a response.

[0012] In the above scheme, the virtual-physical connection interaction mechanism enables the virtual testing and maintenance environment to perceive and control the physical entity testing and maintenance process in real time, including remote fault diagnosis, predictive maintenance and performance optimization. Among them, the virtual-physical connection and interaction mechanism forms a closed-loop control: based on the analysis results of the digital twin, control commands are generated, and the method nodes on the physical entity are called through the OPC UA server to drive the actuator to act, and the status data after execution is fed back to the digital twin for updating.

[0013] In the above scheme, the virtual-physical connection and interaction mechanism enables real-time data perception of the ship testing and maintenance process, ensuring that the virtual environment receives and processes data from physical entities in a timely manner.

[0014] In the above scheme, the OPC UA communication protocol adopts the publish-subscribe model. The virtual environment, as a subscriber, subscribes to variable nodes from the physical layer OPC UA server. The server actively pushes data through the data change notification mechanism. It also adopts a client-server request-response model. The virtual environment, as a client, sends a request to call the method node. The physical server executes the request and returns the result. Reliable transmission via TCP ensures that no instructions are lost and supports instruction priority marking. The MQTT protocol adapts to wide-area, low-bandwidth scenarios through topic layering, QoS grading, and message compression. It uses layered topic transmission with a three-tiered structure of ship ID, device type, and data type. The physical layer edge gateway quickly matches subscribers through topic filtering algorithms, ensuring low message routing time. Furthermore, it uses message compression algorithms to compress low-frequency data before sending. QoS grading ensures data arrives at least once through a publish-acknowledge mechanism, with the number of retransmissions dynamically adjusted based on network packet loss rate. ; in, For the number of retransmissions, For the target reliability, Packet loss rate; High-frequency real-time data is transmitted on the local area network via OPC UA, while low-frequency data is transmitted via MQTT.

[0015] In the above scheme, the virtual-physical connection interaction mechanism adopts the TLS 1.3 protocol for security, uses the AES-256-GCM symmetric encryption algorithm, and the key update cycle and data transmission volume are shown in the following formulas: ; in, For the key update cycle, For maximum update time, For transmission coefficient, To ensure sufficient data volume, the key must be forcibly updated when the data volume reaches a certain amount or at a certain time interval.

[0016] According to a second aspect of the present invention, a ship testing and maintenance method is provided, which performs remote fault diagnosis, predictive maintenance and performance optimization of a ship based on a digital twin, wherein the digital twin is a digital twin constructed according to the ship testing and maintenance process digital twin construction method described in any one of the first aspects.

[0017] According to a third aspect of the present invention, a computer device is provided, comprising: a processor and a memory, the memory storing a program or instructions executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method for constructing a digital twin of a ship testing and maintenance process as described in any one of the first aspects.

[0018] According to a fourth aspect of the present invention, a computer-readable storage medium is provided having a program or instructions stored thereon, which, when executed by a processor, implement the steps of the method for constructing a digital twin of a ship testing and maintenance process as described in any one of the first aspects.

[0019] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: This invention provides a method for constructing a digital twin of the ship testing and maintenance process, aiming to achieve real-time monitoring and intelligent decision support for the entire ship testing and maintenance process. This method constructs a comprehensive, multi-dimensional digital twin to fully describe and characterize the ship testing and maintenance process, ensuring the effective integration and utilization of various information. By constructing an efficient real-time data acquisition framework, it ensures the real-time identification and handling of potential problems during ship operation, greatly improving maintenance efficiency. Furthermore, by constructing an effective virtual-physical connection and interaction mechanism, utilizing protocols such as OPC UA and MQTT, it enables the virtual testing and maintenance environment to effectively perceive real-time data of the physical entity's testing and maintenance process, as well as control the physical entity's testing and maintenance process from the virtual testing and maintenance environment. It possesses capabilities such as remote fault diagnosis and predictive maintenance, effectively improving the intelligence and automation level of the ship testing and maintenance process.

[0020] The specific advantages are as follows: (1) Real-time data monitoring and dynamic model updates have improved the real-time performance, accuracy and efficiency of ship testing and maintenance; (2) By adopting a predictive maintenance strategy, potential faults can be identified in a timely manner, thereby reducing unexpected downtime, improving the overall reliability of the ship, and ensuring the smooth operation of shipping activities; (3) Utilize big data analytics to deeply mine historical and real-time data, optimize maintenance strategies, and reduce maintenance costs. This not only improves resource utilization efficiency but also provides a more economical solution for ship operations, reducing maintenance costs. Attached Figure Description

[0021] Figure 1 This is an overall schematic diagram of a digital twin of a ship testing and maintenance process provided in an embodiment of the present invention; Figure 2 This is a real-time data acquisition and flow framework diagram provided in an embodiment of the present invention; Figure 3 This is a diagram illustrating a virtual-physical connection interaction mechanism provided in an embodiment of the present invention; Figure 4 A diagram of an intelligent decision-making system provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the hardware structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. All other embodiments obtained by those skilled in the art based on the embodiments provided by this invention without inventive effort are within the scope of protection of this invention.

[0023] Obviously, the accompanying drawings described below are merely some examples or embodiments of the present invention. Those skilled in the art can apply the present invention to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this invention, modifications to design, manufacturing, or production based on the technical content disclosed in this invention are merely conventional technical means and should not be construed as insufficient disclosure of the present invention.

[0024] In this invention, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this invention may be combined with other embodiments without conflict.

[0025] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "a," "an," "an," "the," and similar words used in this invention do not indicate quantity limitation and may indicate singular or plural. The terms "comprising," "including," "having," and any variations thereof used in this invention are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms "connected," "linked," "coupled," and similar words used in this invention are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "A plurality" used in this invention refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships may exist; for example, "A and / or B" can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects have an "or" relationship. The terms "first," "second," and "third" used in this invention are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0026] This invention proposes a method for constructing a digital twin for ship testing and maintenance. This method creates a comprehensive digital twin by collecting multi-dimensional feature data from the physical ship object, aiming to achieve real-time monitoring and intelligent decision support throughout the entire ship testing and maintenance process. The method includes constructing a multi-dimensional digital twin, a real-time data acquisition framework, and a virtual-physical connection and interaction mechanism, thereby improving the real-time performance, accuracy, and efficiency of ship testing and maintenance, and meeting the needs of processing massive amounts of heterogeneous data during ship testing and maintenance in the context of intelligent maintenance. Through the construction of this digital twin, the shipbuilding industry will obtain more scientific management and decision-making basis, contributing to the development of intelligent maintenance.

[0027] This invention first proposes a method for constructing a digital twin of the ship testing and maintenance process, specifically a method for simulating and optimizing the ship testing and maintenance process using digital twin technology. This method can accurately simulate the behavior of ships under various testing and maintenance scenarios, providing a powerful decision support tool for ship maintenance and ensuring the efficient and safe operation of ships. The method mainly includes: (1) Constructing multi-dimensional digital twins: such as Figure 1 As shown, a comprehensive digital twin model is constructed by integrating the ship's geometric model, physical characteristics, operational behavior, maintenance rules, and interconnected data. This model can simulate the ship's performance and behavior under different environmental conditions, including the impact of different weather and sea conditions on the ship's performance. This multi-dimensional model not only provides static data of the ship but also dynamically reflects the changes in the ship during actual navigation, providing a more comprehensive perspective for operation and decision-making. The geometric dimension, as the basic framework of the ship's digital twin, needs to accurately map the three-dimensional shape and spatial relationships of the hull and equipment. The Unity engine plays a crucial role in visualization and interactive experience: First, point cloud data of the hull, engine room, and deck equipment are acquired from public sources. After denoising and simplification using point cloud processing software, the data is imported into CAD software (or SolidWorks) to construct a high-precision 3D model (including details such as hull sections, pipe diameters, and equipment installation coordinates). Then, the model is imported into Unity in FBX format, and its mesh optimization tools are used to repair the model structure, ensuring a balance between geometric accuracy and rendering efficiency. For movable parts (such as steering gear rotation and valve switching), skeleton animation is used in Unity. Animation binds model joints, sets keyframe animations to simulate motion trajectories, and uses the PhysX physics engine to assign collision components, enabling spatial interference detection between components (such as simulating collision warnings when maintenance personnel enter a compartment and interact with equipment). Simultaneously, Unity's C# scripting system can link to real-time data. For example, when the physics dimension detects pipe deformation due to pressure, the script dynamically adjusts the mesh vertex positions of the pipe model, visually presenting subtle changes in geometric shape. Users can view local structures through mouse dragging, zooming, and other interactive operations, such as zooming in to view the bolt distribution of the main engine cylinder. Combined with the UI system, equipment numbers, material types, and other attribute information are labeled, making the geometric model not only a static shape mapping but also a visual carrier connecting other dimensions. This provides an intuitive virtual environment for spatial planning in testing and maintenance (such as simulating the placement path of maintenance tools) and component disassembly and assembly simulations. Based on the geometric model, material properties (such as the yield strength of hull steel and the corrosion resistance of pipes) and environmental interaction characteristics (such as wave impact and temperature conductivity) are assigned, simulating the physical behavior of equipment (such as the transmission of main engine vibration and the flow resistance of fuel in pipes).

[0028] (2) Real-time data acquisition framework: such as Figure 2 As shown, sensing devices, including temperature, pressure, and vibration sensors, are deployed, transmitting data to a central processing system via wired or wireless networks. This framework enables real-time monitoring of the ship's key performance indicators and automatically adjusts maintenance strategies based on the monitoring results to optimize operational efficiency and maintenance plans. The real-time data acquisition achieved by this mechanism can also effectively identify potential problems, providing early warnings and handling, thereby improving ship operational efficiency.

[0029] (3) Virtual-real connection interaction mechanism: such as Figure 3 As shown, real-time data exchange between the ship's physical entity and its digital twin is achieved through an OPC UA server, and message transmission is implemented via the MQTT protocol to ensure data timeliness and accuracy. This mechanism enables the virtual testing and maintenance environment to achieve real-time data perception and control of the physical entity's testing and maintenance process, including remote fault diagnosis, predictive maintenance, and performance optimization. The virtual-physical connection interaction mechanism, employing modern protocols such as OPC UA and MQTT, enables real-time data perception of the ship's testing and maintenance process, ensuring that the virtual environment receives and processes data from the physical entity in a timely manner. The OPC UA communication protocol adopts a "publish-subscribe" model. The virtual environment, as a subscriber, subscribes to variable nodes from the physical layer OPC UA server. The server actively pushes data through a "data change notification" mechanism and employs a "client-server" request-response model. The virtual environment, as a client, sends requests to call method nodes, and the physical server executes the requests and returns the results. Reliable TCP transmission ensures no command loss and supports command priority marking. For security, the TLS 1.3 protocol is used, and the AES-256-GCM symmetric encryption algorithm is employed. MQTT adapts to wide-area, low-bandwidth scenarios through "topic layering + QoS grading + message compression". It uses layered topic transmission and adopts a three-level structure of "ship ID-device type-data type". The physical layer edge gateway quickly matches subscribers through a topic filtering algorithm (time complexity O(1)) to ensure low message routing time. Through message compression algorithm, low-frequency data is compressed before sending, reducing message transmission bandwidth. QoS grading ensures that data arrives at least once through a "publish-acknowledge (PUBACK)" mechanism, and the number of retransmissions is dynamically adjusted by the network packet loss rate.

[0030] (4) Intelligent decision support: such as Figure 4 As shown, based on real-time data and a digital twin model, this invention provides ship operators with intelligent maintenance decision support, optimizes maintenance plans, and reduces maintenance costs. By analyzing the combination of historical and real-time data, more precise maintenance strategies can be formulated, ensuring the efficiency and safety of ships during operation.

[0031] Therefore, this invention provides a method for constructing a digital twin of the ship testing and maintenance process, aiming to achieve real-time monitoring and intelligent decision support for the entire ship testing and maintenance process. This method constructs a comprehensive, multi-dimensional digital twin to fully describe and characterize the ship testing and maintenance process, ensuring the effective integration and utilization of various information. By constructing an efficient real-time data acquisition framework, it ensures the real-time identification and handling of potential problems during ship operation, greatly improving maintenance efficiency. Furthermore, by constructing an effective virtual-physical connection and interaction mechanism, utilizing protocols such as OPC UA and MQTT, it enables the virtual testing and maintenance environment to effectively perceive real-time data of the physical entity's testing and maintenance process, as well as control the physical entity's testing and maintenance process from the virtual testing and maintenance environment. It possesses capabilities such as remote fault diagnosis and predictive maintenance, effectively improving the intelligence and automation level of the ship testing and maintenance process.

[0032] Specifically, such as Figure 1 As shown, the method for constructing a digital twin of a ship testing and maintenance process according to an embodiment of the present invention includes the following steps: (1) Construct a comprehensive, multi-dimensional digital twin, including geometric, physical, behavioral, rule-based, and connectivity / interaction dimensions. The geometric dimension involves the shape and structure of the ship, the physical dimension describes material properties and environmental factors, the behavioral dimension covers operation and maintenance activities, the rule-based dimension defines relevant operating procedures, and finally, the connectivity / interaction dimension ensures the efficient flow and integration of information between the various parts. In this way, a comprehensive, multi-dimensional description and characterization of the ship testing and maintenance process can be achieved, ensuring the effective integration and utilization of various types of information; (2) Construct an efficient real-time data acquisition framework, including a perception layer, a transmission layer, and a decision layer, such as Figure 2As shown. The perception layer deploys sensors for temperature, pressure, and vibration around core equipment such as the host and generator, as well as actuators such as fuel regulating valves and cooling fan frequency converters, to capture the real-time operating status of the equipment. The transmission layer adopts an architecture of "edge gateway + redundant industrial Ethernet + satellite / 5G backup link," based on the collaborative transmission of OPC UA and MQTT protocols. High-frequency real-time data (such as host vibration and speed) is converted into OPC UA variable nodes via the edge gateway and pushed with low latency (millisecond level) via industrial Ethernet through a "subscribe-publish" mode, relying on TLS encryption to ensure security and meet real-time synchronization requirements. Low-frequency data (such as operating statistics) is converted into MQTT messages and transmitted via satellite / 5G at QoS=1 level according to hierarchical topics, taking into account bandwidth efficiency. The gateway also supports switching critical commands to OPC in case of failure. UA backup channel and non-emergency data cache resending; the decision-making layer analyzes data through the stream processing engine (such as converting vibration signals into spectrum graphs to identify anomalies), the intelligent diagnostic system combines rule base and machine learning to judge the status, and the decision center generates a response - minor anomalies are pushed to shore-based early warning via MQTT, and in emergency situations (such as a sudden drop in lubrication pressure), the actuator method node is called through OPCUA to trigger operations such as the start of the backup pump. The whole process takes no more than 2 seconds, which greatly improves the reliability and maintenance efficiency of the power system.

[0033] (3) Construct an effective virtual-physical connection and interaction mechanism, such as Figure 3As shown, protocols such as OPC UA and MQTT are used to achieve effective perception of real-time data from the physical entity's testing and maintenance process by the virtual testing and maintenance environment, as well as control of the physical entity's testing and maintenance process by the virtual testing and maintenance environment. OPC UA, as a highly reliable real-time interactive protocol, builds a structured information model based on a TCP / UDP stack, defining object nodes (such as host systems), variable nodes (such as rotational speed and temperature, with a sampling rate of 10ms-1s), and method nodes (such as valve control commands). It adopts a "subscribe-publish" model to achieve real-time push of physical device data to the virtual environment (latency ≤100ms), and completes the issuance of control commands through a "client-server" model (supporting timeout retries), while relying on TLS 1.3 encryption and authentication to ensure security. MQTT, as a lightweight wide-area transmission protocol, is based on the TCP publish-subscribe model, designs layered topics, and encapsulates data containing timestamps and quality identifiers in JSON format. Protocol conversion with OPC UA is achieved through an edge gateway, adapting to historical data uploads and remote command transmission in low-bandwidth scenarios. The two work collaboratively: high-frequency real-time data (such as vibration and rotational speed) is transmitted via OPC UA on the local area network, while low-frequency data (such as statistical values ​​and prediction results) is sent to the shore-based platform via MQTT. This supports remote fault diagnosis (real-time abnormal data is uploaded via OPC UA, and diagnostic results are pushed via MQTT) and predictive maintenance (historical data is used for model training via MQTT, and early warning information is pushed back), forming a closed-loop control of "virtual command - physical execution - data feedback," thereby improving the intelligence level of ship operation and maintenance. This mechanism not only realizes remote fault diagnosis but also supports predictive maintenance, helping operators to identify potential faults in advance and is committed to improving the intelligence and automation level of ship testing and maintenance processes.

[0034] Among them, the multi-dimensional digital twin can comprehensively describe and characterize all aspects of the ship testing and maintenance process, including but not limited to the ship's structure, material properties, operational behavior, and maintenance rules. Specifically, the structural dimension presents the ship's external and internal structure in detail, including the geometry of key components and their interrelationships; the material property dimension covers the performance characteristics of different materials, such as strength, corrosion resistance, and thermal conductivity; the operational behavior dimension records and analyzes the ship's operating modes, operator behavior, and typical usage scenarios; and the maintenance rules dimension focuses on various maintenance strategies and standard operating procedures, providing precise guidance for maintenance operations and maintenance. Geometric dimensions, as the foundational framework of a ship's digital twin, require precise mapping of the hull and equipment's three-dimensional form and spatial relationships. The Unity engine plays a crucial role in visualization and interactive experience: First, point cloud data of the hull, engine room, and deck equipment is acquired from publicly available sources. After denoising and simplification using point cloud processing software, this data is imported into CAD software (or SolidWorks) to construct a high-precision 3D model (including details such as hull sections, pipe diameters, and equipment installation coordinates). Then, this model is imported into Unity in FBX format, where its mesh optimization tools are used to repair the model structure, ensuring a balance between geometric accuracy and rendering efficiency. For movable components (such as steering gear rotation and valve switching), skeleton animation is used in Unity. Animation binds model joints, sets keyframe animations to simulate motion trajectories, and uses the PhysX physics engine to assign collision components, enabling spatial interference detection between components (such as simulating collision warnings when maintenance personnel enter a compartment and interact with equipment). Simultaneously, Unity's C# scripting system can link to real-time data. For example, when the physics dimension detects pipe deformation due to pressure, the script dynamically adjusts the mesh vertex positions of the pipe model, visually presenting subtle changes in geometric shape. Users can view local structures through mouse dragging, zooming, and other interactive operations, such as zooming in to view the bolt distribution of the main engine cylinder. Combined with the UI system, equipment numbers, material types, and other attribute information are labeled, making the geometric model not only a static shape mapping but also a visual carrier connecting other dimensions. This provides an intuitive virtual environment for spatial planning in testing and maintenance (such as simulating the placement path of maintenance tools) and component disassembly and assembly simulations. Based on the geometric model, material properties (such as the yield strength of hull steel and the corrosion resistance of pipes) and environmental interaction characteristics (such as wave impact and temperature conductivity) are assigned, simulating the physical behavior of equipment (such as the transmission of main engine vibration and the flow resistance of fuel in pipes). The technical approach includes obtaining physical parameters through material testing, establishing mechanical and thermodynamic simulation models using finite element analysis software (ANSYS, ABAQUS), and simulating fluid motion using CFD (computational fluid dynamics) to achieve real-time calculation and prediction of physical processes such as equipment wear and structural deformation.This system depicts the dynamic operation and maintenance activities of ships and equipment, such as main engine start / stop procedures, valve opening and closing sequences, and periodic maintenance steps, and correlates these with changes in equipment status (e.g., the dynamic response of fuel consumption when engine speed increases). Technically, a state machine model is used to describe the equipment's behavioral logic. Historical operation data is recorded through a time-series database, and typical behavioral patterns are extracted from maintenance logs using process mining algorithms. The Unity simulation engine is used to visualize and reproduce the operation process, supporting virtual rehearsals of maintenance steps. A rule model, based on equipment operating procedures, technical maintenance manuals, fault handling specifications, and alarm response procedures, forms an executable rule base to constrain the behavioral logic and decision-making processes of the digital twin. The technical approach involves constructing a rule semantic framework through ontology modeling and using a business rule engine to transform natural language rules into machine-recognizable logical expressions, such as "When the main engine cylinder temperature > 100℃, it is recommended to start the cooling system," enabling dynamic rule invocation and updates. A cross-dimensional data flow and collaboration mechanism is constructed to achieve parameter linkage between the geometric model and physical simulation, and trigger interaction between behavioral data and the rule base. The technical approach relies on the OPC UA protocol to establish a unified data interface, which connects real-time sensor data, such as temperature and pressure, to the digital twin platform. It achieves asynchronous communication of multi-dimensional data through message queues and integrates the relationships between various dimensions using knowledge graphs (such as the mapping of "geometric location-physical parameters-maintenance behavior"), supporting cross-dimensional queries and analysis (such as locating the physical cause of pressure anomalies based on the geometric location of a pipeline).

[0035] The real-time data acquisition framework boasts powerful data acquisition capabilities, enabling real-time acquisition of data during ship testing and maintenance processes. This data is then transmitted to the feedback layer via a data flow network for decision-making, achieving rapid response. The perception layer is directly deployed on the physical ship, deeply integrating sensors and actuators with key ship equipment components to form a "physical acquisition-virtual synchronization" data interaction link. Physical sensors, such as temperature, pressure, and vibration sensors, are installed on physical components like the main engine cylinder, bearings, and fuel lines, matching the equipment's operating conditions. Simultaneously, virtual perception nodes with consistent parameters are configured on corresponding virtual components in the ship's digital twin model. After the physical sensors acquire real-time equipment operating data, it is synchronously transmitted to the virtual perception nodes via data interfaces, dynamically updating the state parameters of the digital twin model to ensure real-time consistency between the virtual model and the physical equipment's state. Furthermore, a one-to-one mapping is established between physical actuators and virtual actuators in the digital twin model. Operational commands generated by virtual actuators can be directly synchronized to physical actuators, achieving closed-loop control of "virtual command-physical execution." A highly reliable architecture with protocol coordination and link redundancy is constructed at the transmission layer. Data acquired by physical sensors is first aggregated to the data edge gateway via the ship's local industrial bus. The gateway incorporates a multi-protocol conversion module. For high-frequency real-time data such as host speed and bearing vibration, variable sections are defined according to the OPC UA information model. Data is pushed via redundant industrial Ethernet using a "publish-subscribe" model, encrypted with TLS 1.3, and access control lists (ACLs) restrict read / write permissions to ensure low-latency delivery to the feedback layer. Simultaneously, a 128GB local cache is built into the edge gateway. When the main link is interrupted, non-urgent data is automatically stored and resent in batches via MQTT after network recovery. Critical control commands are switched to the backup channel to ensure stable command transmission. The feedback layer analyzes data through a visual interface of the digital twin model. In the host virtual scene built in Unity, when vibration spectrum analysis identifies anomalies, the corresponding virtual bearing is directly located and highlighted. The intelligent diagnostic system combines the physical simulation results of the virtual model to generate decisions, issuing commands by calling the method nodes of the virtual actuators to synchronously drive the physical actuators.Taking a virtual turbocharger of a ship's main engine as an example: physical temperature sensors and physical vibration sensors are installed on components such as the turbine impeller, compressor housing, and bearing housing of the ship's physical power system. The physical sensors collect operating data in real time and synchronize it to the corresponding virtual components in the digital twin model of the turbocharger. In the virtual model, temperature distribution cloud maps and vibration waveforms can be dynamically displayed. When the transmission layer transmits data showing that the vibration peak of the physical bearing exceeds the standard through OPC UA, the bearing component in the virtual model immediately shows a red warning state. The decision layer, combined with the flow field simulation of the virtual model, determines that the dynamic imbalance is caused by carbon buildup on the impeller. The decision center calls the cleaning command method node of the virtual turbocharger and synchronously issues a cleaning agent injection command to the actuator of the physical turbocharger. Throughout the process, the data interaction and status feedback between the virtual model and the physical equipment are completely synchronized, realizing precise monitoring and control based on the virtual model.

[0036] The virtual-physical connection interaction mechanism, employing modern protocols such as OPC UA and MQTT, enables real-time data awareness of ship testing and maintenance processes, ensuring that the virtual environment receives and processes data from physical entities in a timely manner. OPC UA, through a three-layer architecture of "information model + communication mode + security layer," achieves highly reliable real-time data transmission and control between physical entities and the virtual environment. It uses a "node-attribute-reference" structure to describe device status and operation, where the sampling rate and data update logic of variable nodes are constrained by the following formula: ; in, It is a change in a physical quantity. This represents the sampling interval. It indicates that data is pushed when the physical quantity change exceeds a threshold or the sampling time reaches a certain interval.

[0037] The OPC UA communication protocol adopts a "publish-subscribe" model. The virtual environment, acting as a subscriber, subscribes to variable nodes from the physical layer OPC UA server. The server actively pushes data through a data change notification mechanism. It also employs a "client-server" request-response model, where the virtual environment, acting as a client, sends requests to invoke method nodes. The physical server executes these requests and returns the results. Reliable TCP transmission ensures no command loss and supports command priority marking. For security, it uses the TLS 1.3 protocol, and the symmetric encryption algorithm is AES-256-GCM. The key update cycle and data transmission volume are shown in the following formula: ; in, For the key update cycle, For maximum update time, For transmission coefficient, To ensure sufficient data volume, the key must be forcibly updated when the data volume reaches a certain amount or at a certain time interval.

[0038] MQTT adapts to wide-area, low-bandwidth scenarios through "topic layering + QoS grading + message compression". It uses layered topic transmission and adopts a three-level structure of "ship ID-device type-data type". The physical layer edge gateway quickly matches subscribers through a topic filtering algorithm (time complexity O(1)) to ensure low message routing time. Through message compression algorithm, low-frequency data is compressed before sending to reduce message transmission bandwidth. QoS grading ensures that data arrives at least once through a "publish-acknowledge (PUBACK)" mechanism, and the number of retransmissions is dynamically adjusted by the network packet loss rate. ; in, For the number of retransmissions, For the target reliability, This refers to the packet loss rate. When the packet loss rate reaches 5%, N reaches 3, which satisfies the requirement.

[0039] Based on the aforementioned method for constructing a digital twin of the ship testing and maintenance process, this invention also provides a ship testing and maintenance method. This method, based on the aforementioned constructed digital twin, performs remote fault diagnosis, predictive maintenance, and performance optimization of the ship, specifically including the following steps: (1) Data acquisition stage: Sensors installed in key parts of the ship are used to monitor the ship's operating status in real time, including but not limited to engine performance parameters, hull structural stress, ship position and environmental conditions (such as wind speed and wave height). The data collected by the sensors is then transmitted to the data acquisition unit inside the ship via a wireless communication network.

[0040] (2) Data preprocessing stage: The data acquisition device preprocesses the collected raw data, including filtering, data cleaning and formatting, to facilitate subsequent processing and analysis.

[0041] (3) Digital twin construction stage: The preprocessed data is sent to the digital twin server via the network. The software platform running on the server integrates geometric, physical, behavioral and rule data to construct a multi-dimensional digital twin of the ship.

[0042] (4) Real-time monitoring and analysis phase: The digital twin server updates the status of the digital twin in real time and predicts the performance and behavior of the ship under current and future environmental conditions through simulation algorithms. Furthermore, it uses a virtual-real connection interaction mechanism to compare and analyze the status and prediction results of the digital twin with the actual ship's operating data.

[0043] (5) Intelligent Assessment and Decision Support Stage: The intelligent assessment system receives data from the digital twin server and, in conjunction with historical maintenance records and an expert knowledge base, assesses the ship's health status, such as... Figure 4 As shown, the system automatically generates maintenance suggestions and operation instructions based on the assessment results and presents them to maintenance personnel.

[0044] This invention improves the real-time performance, accuracy, and efficiency of ship testing and maintenance through real-time data monitoring and dynamic model updates; it employs predictive maintenance strategies to promptly identify potential faults, thereby reducing unexpected downtime, improving overall ship reliability, and ensuring the smooth operation of shipping activities; and it utilizes big data analytics to deeply mine historical and real-time data, optimizing maintenance strategies and reducing maintenance costs. This not only improves resource utilization efficiency but also provides a more economical solution for ship operations, lowering maintenance costs.

[0045] It should be noted that the steps shown in the above process or in the flowchart of the accompanying figures can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0046] Combination Figure 1 The method for constructing a digital twin of a ship testing and maintenance process described in this embodiment of the invention can be implemented using a computer device. Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Figure 5 As shown, the device may include a processor 301 and a memory 302 storing computer program instructions.

[0047] Specifically, the processor 301 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of the present invention.

[0048] Memory 302 may include a large-capacity memory for data or instructions. For example, and not limitingly, memory 302 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), flash memory, an optical disk drive, a magneto-optical disk drive, magnetic tape, or a Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 302 may include removable or non-removable (or fixed) media. Where appropriate, memory 302 may be internal or external to a data processing device. In a particular embodiment, memory 302 is non-volatile memory. In a particular embodiment, memory 302 includes read-only memory (ROM) and random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable read-only memory (PROM), an erasable read-only memory (EPROM), an electrically erasable read-only memory (EEPROM), an electrically alterable read-only memory (EAROM), or flash memory, or a combination of two or more of these. Where appropriate, the RAM can be Static Random-Access Memory (SRAM) or Dynamic Random-Access Memory (DRAM). DRAM can be Fast Page Mode Dynamic Random Access Memory (FPMDRAM), Extended Data Out Dynamic Random Access Memory (EDODRAM), Synchronous Dynamic Random-Access Memory (SDRAM), etc.

[0049] The memory 302 can be used to store or cache various data files that need to be processed and / or communicated, as well as possible computer program instructions executed by the processor 301.

[0050] The processor 301 reads and executes computer program instructions stored in the memory 302 to implement any of the methods for constructing a digital twin of a ship testing and maintenance process in the above embodiments.

[0051] In some embodiments, the computer device may further include a communication interface 303 and a bus 300. For example, Figure 5 As shown, the processor 301, memory 302, and communication interface 303 are connected through bus 300 and complete communication with each other.

[0052] The communication interface 303 is used to enable communication between the various modules, devices, units, and / or equipment in the embodiments of the present invention. The communication interface 303 can also enable data communication with other components such as external devices, image / data acquisition devices, databases, external storage, and image / data processing workstations.

[0053] Bus 300 includes hardware, software, or both, that couples components of a computer device together. Bus 300 includes, but is not limited to, at least one of the following: data bus, address bus, control bus, expansion bus, and local bus. For example, and not as a limitation, bus 300 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 300 may include one or more buses. Although specific buses are described and illustrated in the embodiments of the present invention, the present invention is contemplated by any suitable bus or interconnect.

[0054] The computer device can execute the digital twin construction method for ship testing and maintenance processes in this embodiment of the invention, thereby achieving a combination of Figure 1 The method for constructing digital twins of ship testing and maintenance processes is described.

[0055] Furthermore, in conjunction with the digital twin construction method for ship testing and maintenance processes described in the above embodiments, this invention can be implemented using a computer-readable storage medium. This computer-readable storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the digital twin construction methods for ship testing and maintenance processes described in the above embodiments.

[0056] In summary, this invention, by constructing a virtual model of a ship using a data twin, can effectively achieve efficient ship maintenance. Combined with real-time data interaction and simulation analysis, it can effectively address the pain points of traditional maintenance methods. The digital twin model collects real-time operational status data of the physical ship through sensors, synchronously feeding this data back to the virtual model. Combined with a historical database, it assesses the ship's condition and provides maintenance suggestions, enabling real-time fault warnings, eliminating the need for periodic inspections, and reducing safety risks and maintenance costs.

[0057] It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments have been described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. In addition, depending on the implementation needs, the various steps / components described in this invention can be broken down into more steps / components, or two or more steps / components or parts of steps / components can be combined into new steps / components to achieve the purpose of this invention.

[0058] It will be readily understood by those skilled in the art that the above-described embodiments merely illustrate several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A method for constructing a digital twin of a ship testing and maintenance process, characterized in that, The method includes: (1) Constructing a multi-dimensional digital twin: Integrating the ship's geometric model, physical characteristics, operational behavior, maintenance rules, and connection interaction data to construct a multi-dimensional digital twin model of the ship, so as to simulate the ship's performance and behavior under different environmental conditions; wherein, the multi-dimensional digital twin includes geometric dimension, physical dimension, behavioral dimension, rule dimension, and connection interaction dimension; the connection interaction dimension is used to realize parameter linkage and state synchronization between different dimension models; (2) Establish a data acquisition framework: Deploy sensing devices to monitor the key performance indicators of the ship in real time and transmit real-time data through wired or wireless networks; (3) Construct a virtual-physical connection and interaction mechanism: Real-time data exchange between the physical entity of the ship and the digital twin is realized through the OPC UA server, and message transmission is realized through the MQTT protocol; (4) Provide intelligent decision support: Based on real-time data and digital twins, combined with historical data and expert knowledge base, generate maintenance suggestions and decision support information.

2. The method for constructing a digital twin of a ship testing and maintenance process according to claim 1, characterized in that, Building a multi-dimensional digital twin includes: The process involves acquiring point cloud data of the ship, denoising and simplifying it, and then importing it into CAD or SolidWorks software to build a high-precision 3D model. This model is then imported into the Unity engine to utilize mesh optimization tools to repair the model structure. For movable parts, the model joints are bound in Unity using skeletal animation, keyframe animations are set to simulate motion trajectories, and collision body components are assigned using the physics engine to achieve spatial interference detection between parts. Unity's C# scripting system is used to correlate real-time data to adjust the model. Based on the geometric model, material properties and environmental interaction characteristics are assigned to simulate the physical behavior of the equipment.

3. The method for constructing a digital twin of a ship testing and maintenance process according to claim 1, characterized in that, The data acquisition framework monitors key performance indicators of the vessel in real time and automatically adjusts maintenance strategies based on the monitoring results to optimize the vessel's operational efficiency and maintenance schedule, including: The perception layer captures real-time device operating status data based on sensors; The transport layer, including the edge gateway, is used to convert sensor data into OPCUA variable nodes or MQTT messages according to its real-time requirements and data frequency, and select the appropriate local industrial network or remote wireless network for transmission. The decision-making layer analyzes data through a stream processing engine, combines a rule base with machine learning to determine the state, and generates a response.

4. The method for constructing a digital twin of a ship testing and maintenance process according to claim 1, characterized in that, The virtual-physical connection and interaction mechanism enables the virtual testing and maintenance environment to perceive and control the physical entity testing and maintenance process in real time, including remote fault diagnosis, predictive maintenance and performance optimization; Among them, the virtual-physical connection and interaction mechanism forms a closed-loop control: based on the analysis results of the digital twin, control commands are generated, and the method nodes on the physical entity are called through the OPC UA server to drive the actuator to act, and the status data after execution is fed back to the digital twin for updating.

5. The method for constructing a digital twin of a ship testing and maintenance process according to claim 4, characterized in that, The virtual-physical connection and interaction mechanism enables real-time data perception of the ship testing and maintenance process, ensuring that the virtual environment receives and processes data from physical entities in a timely manner.

6. The method for constructing a digital twin of a ship testing and maintenance process according to claim 1, characterized in that, The OPCUA communication protocol adopts a publish-subscribe model. The virtual environment, as a subscriber, subscribes to variable nodes from the physical layer OPC UA server. The server actively pushes data through a data change notification mechanism. It also adopts a client-server request-response model. The virtual environment, as a client, sends a request to call a method node. The physical server executes the request and returns the result. Reliable transmission via TCP ensures that no instructions are lost and supports instruction priority marking. The MQTT protocol adapts to wide-area, low-bandwidth scenarios through topic layering, QoS grading, and message compression. It uses layered topic transmission with a three-tiered structure of ship ID, device type, and data type. The physical layer edge gateway quickly matches subscribers through topic filtering algorithms, ensuring low message routing time. Furthermore, it uses message compression algorithms to compress low-frequency data before sending. QoS grading ensures data arrives at least once through a publish-acknowledge mechanism, with the number of retransmissions dynamically adjusted based on network packet loss rate. ； in, For the number of retransmissions, For the target reliability, Packet loss rate; High-frequency real-time data is transmitted on the local area network via OPC UA, while low-frequency data is transmitted via MQTT.

7. The method for constructing a digital twin of a ship testing and maintenance process according to claim 6, characterized in that, The virtual-physical connection interaction mechanism adopts the TLS 1.3 protocol for security and uses the AES-256-GCM symmetric encryption algorithm. The key update cycle and data transmission volume are shown in the following formula: ； in, For the key update cycle, For maximum update time, For transmission coefficient, To ensure sufficient data volume, the key must be forcibly updated when the data volume reaches a certain amount or at a certain time interval.

8. A method for testing and maintaining a ship, characterized in that, This method enables remote fault diagnosis, predictive maintenance, and performance optimization of ships based on digital twins, wherein the digital twin is constructed by the method for constructing digital twins of ship testing and maintenance processes according to any one of claims 1 to 7.

9. A computer device, characterized in that, include: A processor and a memory, wherein the memory stores a program or instructions that can run on the processor, and when the program or instructions are executed by the processor, implement the steps of the method for constructing a digital twin of a ship testing and maintenance process as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores programs or instructions that, when executed by a processor, implement the steps of the digital twin construction method for ship testing and maintenance processes as described in any one of claims 1 to 7.

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