Ship data semantic interoperation method oriented to heterogeneous CAD (Computer Aided Design) integration
By constructing a semantic ontology and semantic mapping rules for ship products, the problem of data exchange between heterogeneous CAD systems was solved, achieving complete preservation of design intent and seamless data flow, thereby improving the digitalization and intelligence level of the shipbuilding industry.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-23
- Publication Date
- 2026-03-27
AI Technical Summary
In existing technologies, data exchange between heterogeneous CAD systems leads to the loss of design intent, resulting in information silos, and the low accuracy of feature recognition makes it unable to cope with complex design scenarios.
A semantic ontology of ship products is constructed, and the original feature data is converted into intermediate data files through semantic mapping rules. An equivalent model is then reconstructed in the target CAD system, and multi-level consistency verification is performed.
It achieves complete preservation of design intent, breaks down information silos, enhances data reuse value and collaboration efficiency, reduces R&D costs, and supports digital twins and intelligent manufacturing.
Smart Images
Figure CN121744510A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of computer-aided design and ship engineering, and particularly relates to a ship data semantic interoperability method for heterogeneous CAD integration. BACKGROUND
[0002] The shipbuilding industry is a technology-intensive industry, and its design and manufacturing process is extremely complex, involving ship body, machinery, electrical, piping and other multiple specialties, and usually multiple CAD (Computer-Aided Design) software such as CATIA (Computer-Aided Three-Dimensional Interactive Application), AVEVA Marine, AutoCAD (Automatic CAD), SolidWorks (three-dimensional mechanical design software) and the like need to be used in collaboration, and such heterogeneous CAD systems have significant differences in data bottom structure, feature definition and geometric representation.
[0003] Currently, the exchange of data between heterogeneous CAD systems mainly relies on neutral file formats such as STEP (Standard for the Exchange of Product model data) and IGES (Initial Graphics Exchange Specification), and since such standard formats mainly focus on the exchange of geometric information, the high-level design information such as design history, parameterized features, constraint relationships and manufacturing-related attributes (i.e. "design intent") are often lost in the conversion process, and the converted model is thus degraded to a "dumb geometry" entity, losing its parameterized editability, which seriously restricts the downstream design, analysis and manufacturing process. The inherent defects of this data exchange form a serious "information island", making the data unable to flow smoothly in the whole life cycle of ship concept design, detailed design, production and maintenance, and engineers need to spend a lot of time on manual data conversion and model reconstruction, which not only is inefficient, but also is prone to errors, increasing the design and manufacturing cost.
[0004] The prior art usually solves such technical problems through feature recognition technology or higher-level STEP application protocols such as AP242 (Application Protocol 242), but the accuracy and coverage of feature recognition are limited, and it cannot cope with all complex design scenarios. SUMMARY
[0005] To address the issues of semantic information loss, inability to convey design intent, and poor data reusability leading to information silos in existing technologies, and to overcome the limitations of current technology in terms of low feature recognition accuracy and limited coverage, thus failing to handle complex design scenarios, this invention aims to provide a semantic interoperability method for ship data in heterogeneous CAD integration. The specific technical solution adopted is as follows: Construct a semantic ontology for ship products; and obtain a source CAD system containing hull segment models, and extract raw feature data by calling the application programming interface of the source CAD system based on the hull segment models; Based on the semantic ontology of ship products, semantic mapping rules are established from the features of the source CAD system to the ontology concepts. The original feature data is then converted into intermediate data files through the semantic mapping rules. The target CAD system is acquired, intermediate data files are parsed, and a local 3D model equivalent to the source CAD system is reconstructed in the target CAD system. Perform multi-level consistency checks on the local 3D model to achieve data interoperability.
[0006] Preferably, the semantic ontology of ship products is constructed, including: Collect knowledge in the shipbuilding field and extract descriptions of core design concepts, terminology, classification systems, design rules, and constraints for ship products; Based on the description, define the top-level concepts and subclass levels sequentially to build the model, and define the corresponding data attributes and object attributes based on the top-level concepts and / or subclass levels to construct the domain knowledge base.
[0007] Preferably, the data attributes are used to describe the parameters of the ship products; the object attributes are used to describe the relationships between the ship products.
[0008] Preferably, the original feature data is extracted by calling the application programming interface of the source CAD system based on the hull section model, specifically as follows: The application programming interface of the source CAD system is called to traverse the design history tree corresponding to the hull section model, extract geometric topology information and high-level semantic information. The geometric topology information includes geometric primitives, geometric parameters, dimensions applied to the geometric primitives, and geometric constraints. The high-level semantic information includes feature definitions, design parameters, assembly constraints, material information, and custom metadata. The geometric topology information and high-level semantic information are integrated to form a set of data objects as the original feature data.
[0009] Preferably, based on the semantic ontology of ship products, semantic mapping rules are established from the features of the source CAD system to the ontology concepts. These semantic mapping rules are then used to convert the original feature data into intermediate data files, including: Obtain a semantic mapping engine containing a semantic mapping rule base, define semantic mapping rules from source CAD system features to ontology concepts based on the semantic mapping rule base, and perform parameter mapping and constraint mapping in sequence; Based on the semantic mapping rule base after the mapping is completed, the original feature data is processed, ontology concepts are instantiated, corresponding attributes are populated, and the data is converted into intermediate data files.
[0010] Preferably, the intermediate data file adopts either XML or JSON format, and serves as a neutral carrier for information exchange, independent of the source CAD system.
[0011] Preferably, parsing the intermediate data file and reconstructing a local 3D model equivalent to the source CAD system in the target CAD system includes: The intermediate data file is parsed by the target CAD system and deserialized into an object model in the memory of the target CAD system, and the object model has the same structure as the source CAD system. Based on the target CAD system, reverse mapping and command generation are performed to clarify the feature dependencies and construction order of intermediate data file records; By following the feature dependencies and construction order recorded in the intermediate data files, a local 3D model equivalent to the source CAD system is reconstructed in the target CAD system.
[0012] Preferably, reverse mapping and command generation are performed based on the target CAD system to clarify the feature dependencies and construction order of intermediate data file records, specifically as follows: Pre-defined reverse semantic mapping rules are used to translate ontology concepts into application programming interface (API) call sequences of the target CAD system. Based on the API call sequences, the corresponding information stored in the intermediate data files is obtained to determine feature dependencies and construction order.
[0013] Preferably, multi-level consistency checks are performed on the local 3D model to complete data interoperability, specifically as follows: Based on the local 3D model, geometric verification, semantic verification, and structural verification are performed sequentially to generate verification results. The verification results are then generated into a report and fed back to the user, thus completing data interoperability.
[0014] To address the aforementioned problems, the present invention also provides an electronic device comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus, and the processor invokes logical instructions in the memory to execute the aforementioned method for semantic interoperability of ship data for heterogeneous CAD integration.
[0015] The present invention has the following beneficial effects: 1. By integrating the semantic ontology of ship products and the original feature data, that is, by delving into the feature level of the CAD model and using the semantic ontology as a bridge, the design intent is fully preserved. This allows the reconstructed model to have complete engineering semantics in the target CAD system and to be directly editable, greatly enhancing the reusability value of the design data. By providing a scalable and universal data exchange framework independent of specific CAD vendors, it effectively breaks down information silos caused by software heterogeneity, enabling seamless data flow throughout the entire ship lifecycle. Furthermore, it replaces the traditional, inefficient, and error-prone manual model reconstruction work with an automated data conversion process, significantly improving collaboration efficiency and reducing R&D costs. Specifically, it directly extracts raw feature data by calling the application programming interface of the source CAD system. This deterministic data acquisition method fundamentally eliminates the ambiguity and uncertainty inherent in feature recognition technology, ensuring high semantic accuracy. Simultaneously, the scalable and universal data exchange framework, namely the ship product semantic ontology and semantic mapping rules, addresses the limitation of coverage. It decouples the data extraction and data reconstruction processes. When faced with new or complex ship design features, it only requires defining new concepts and configuring corresponding mapping rules in the ontology to support them, without needing to reconstruct the system. This allows it to broadly cover various heterogeneous CAD systems and complex engineering semantic scenarios. Furthermore, the intermediate data files generated based on the semantic ontology of ship products and the original feature data, namely the high-fidelity model data rich in complete semantics, have laid a solid foundation for building a "digital twin" for the shipbuilding industry. This has strongly supported advanced application scenarios such as virtual assembly, performance simulation, and intelligent manufacturing, and promoted the digital and intelligent transformation of the shipbuilding industry.
[0016] 2. The electronic device provided by this invention has the same beneficial effects as the semantic interoperability method for ship data for heterogeneous CAD integration provided by this invention, and will not be elaborated here. Attached Figure Description
[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 The flowchart illustrates the steps of a method for semantic interoperability of ship data for heterogeneous CAD integration, as provided in one embodiment of the present invention. Figure 2 This is a schematic diagram of the architecture of a method for semantic interoperability of ship data for heterogeneous CAD integration, provided in one embodiment of the present invention. Detailed Implementation
[0019] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method for semantic interoperability of ship data for heterogeneous CAD integration proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.
[0020] Unless otherwise defined, 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.
[0021] The following description, in conjunction with the accompanying drawings, details a specific scheme for a semantic interoperability method for ship data oriented towards heterogeneous CAD integration provided by the present invention.
[0022] Please combine Figure 1 and Figure 2 This document illustrates a flowchart and architecture diagram of a method for semantic interoperability of ship data for heterogeneous CAD integration, provided by an embodiment of the present invention. The method includes: Step S1: Construct the semantic ontology of the ship product; and obtain the source CAD system containing the hull section model, and extract the original feature data by calling the application programming interface of the source CAD system based on the hull section model; Step S2: Based on the semantic ontology of ship products, establish semantic mapping rules from source CAD system features to ontology concepts, and convert the original feature data into intermediate data files through semantic mapping rules; Step S3: Obtain the target CAD system, parse the intermediate data file, and reconstruct a local 3D model in the target CAD system that is equivalent to the source CAD system; Step S4: Perform multi-level consistency verification on the local 3D model to complete data interoperability.
[0023] To better illustrate, a CAD system, or Computer-Aided Design system, is a software tool that utilizes computer technology for design work. In the shipbuilding industry, information silos arise from the scattered information across different CAD systems, resulting in semantic information loss, inability to convey design intent, and poor data reusability. Therefore, it is necessary to unify and map the scattered geometric data and non-geometric semantic information such as design specifications, material properties, manufacturing process requirements, and assembly relationships from different CAD systems. This enables deep data understanding and sharing across platforms and systems, achieving high-fidelity, semantically complete bidirectional conversion between heterogeneous CAD systems. This provides an efficient and reliable data integration solution for the digital management of ship design, manufacturing, simulation, and even the entire lifecycle.
[0024] Understandably, the purpose of constructing a semantic ontology for ship products is to build a semantic ontology that can uniformly describe knowledge in the ship domain, providing a unified and unambiguous semantic reference standard for all subsequent data transformations and integrations.
[0025] Further, in step S1, the semantic ontology of the ship product is constructed, including: Step S11: Collect knowledge in the field of shipbuilding and extract descriptions of the core design concepts, terminology, classification system, design rules and constraints of ship products.
[0026] To clarify, ship design experts, process engineers, and information technology experts were organized to jointly collect and compile design specifications from authoritative organizations such as the China Classification Society (CCS) and Det Norske Veritas (DNV), as well as product data exchange standards from the International Organization for Standardization (ISO), such as ISO 10303-STEP (Standard for the Exchange of Product Model). This study systematically extracts core design concepts, terminology, classification systems, design rules, and constraints for shipbuilding products across various disciplines, including data, internal design manuals, drawing specifications, and glossaries. Core design concepts refer to the fundamental and guiding design ideas and theoretical basis within the shipbuilding field. Terminology encompasses standardized and regulated vocabulary and expressions used in the design and communication process within the shipbuilding profession. The classification system refers to the hierarchical and systematic organization and division of ship design elements based on dimensions such as function, structure, or attributes. Design rules are the technical standards, industry norms, and general principles that must be followed during the design process. Constraints describe the interrelationships, dependencies, or collaborations between different design parameters, professional modules, or system components.
[0027] It should be further clarified that the reference to the design manuals used internally by the enterprise is considered internal document, and its use could potentially lead to data leaks during ontology construction. In practice, a layered architecture strategy of "general core ontology + private extended ontology" is adopted to prevent data leaks. Specifically, this layered construction addresses both leaks and interoperability, including a general layer and a private layer. In the general layer, a core ontology is built based on publicly available standards such as CCS, DNV, and ISO, serving as the industry-standard data exchange foundation. In the private layer, the enterprise's internal manuals are used only to build the enterprise's unique private extended ontology, defining only the "structure" of private characteristics and deployed only within the enterprise's intranet environment. Access control is employed to ensure that only authorized internal systems can access the internal manuals, supporting configuration loading policies. During data exchange, only authorized internal systems can load and parse the semantics in the "private extended ontology," such as by inputting specific codes or keys; otherwise, the system only exchanges general layer data, effectively protecting the security of sensitive enterprise data and private structural information.
[0028] Step S12: Define the top-level concept and subclass hierarchy in sequence according to the description to perform modeling, and define the corresponding data attributes and object attributes based on the top-level concept and / or subclass hierarchy to build a domain knowledge base.
[0029] Specifically, firstly, the concept categories and hierarchical relationships are defined. This involves defining the top-level concept and subclass hierarchy sequentially according to the description in step S11 above, where concept categories are used to construct the ontology skeleton (i.e., Class and subClassOf). In this embodiment, an ontology editing tool, such as Stanford University's Protégé, is used, employing a formal ontology description language recommended by the W3C (World Wide Web Consortium), such as OWL (Web Ontology). (Language, i.e., the web ontology language); then, define top-level concepts, such as ShipProduct, DesignFeature, Attribute, Constraint, etc.; next, construct subclass hierarchy based on any top-level concept. For example, under DesignFeature, construct detailed subclass hierarchy, such as HullFeature, which includes HullPlate, Stiffener, Manhole, etc.; and under the subclass PipingFeature, which includes PipeSegment, Flange, Valve, Elbow, etc. That is, HullFeature and PipingFeature are parallel, each representing a different professional field, and both inherit from the top-level concept DesignFeature; classes are connected through subClassOf (is a type of...) relationships to build an inheritance system, forming a tree-like, logically rigorous conceptual structure.
[0030] Based on the top-level concept and / or subclass hierarchy, the corresponding data properties and object properties are defined. That is, for each class at each level of the top-level concept and subclass hierarchy, the data properties and object properties are precisely defined. They follow the inheritance principle. Among them, the data properties and object properties include common properties, such as name and creation time, which are defined at the top-level concept; special properties, such as thickness and material, are defined at the corresponding subclass hierarchy.
[0031] Furthermore, data attributes are used to describe the parameters of ship products; object attributes are used to describe the relationships between ship products.
[0032] It can be explained that, in this embodiment, ship products are used to describe entities, that is, data attributes are used to describe the specific parameters of the entities, and object attributes are used to describe the complex relationships between entities; the definition logic of the two attributes follows the triple structure of ontology, where the data attribute is who (Subject) has the feature (Predicate) and the corresponding value type (Object); the object attribute is who (Subject) has the relationship (Predicate) with whom (Object); by defining data attributes and object attributes, non-geometric engineering semantics are closely associated with the design entities.
[0033] To better illustrate this, examples are given based on data attributes and object attributes. For instance, for the HullPlate subclass, we define the data attributes hasThickness (with a value of float) and hasMaterialGrade (with a value of string); for the Stiffener subclass, we define the object attribute isWeldedTo (with a value of the HullPlate class) to formally express the welding relationship between the stiffener and the hull plate. This means explicitly defining the implicit geometric positional relationship between the stiffener and the hull plate, which may have geometric contact, as a welding assembly relationship, ensuring that the computer can understand the design intent such as manufacturing processes, and not just the shape; and we define the isConnectedTo relationship between PipeSegments.
[0034] Understandably, the source CAD system is either Dassault Systèmes' CATIA V5 (Computer Aided Three-dimensional Interactive Application Version 5) or Siemens' NX (Unigraphics NX). Data semantic parsing and extraction are performed on the source CAD system. When it is necessary to convert a hull section model designed in the source CAD system, the user initiates the data parsing and extraction operation that is deeply integrated with the system.
[0035] Further, in step S1, the original feature data is extracted by calling the application programming interface of the source CAD system based on the hull section model, specifically as follows: The application programming interface of the source CAD system is called to traverse the design history tree corresponding to the hull section model, extract geometric topology information and high-level semantic information. Geometric topology information includes geometric primitives, geometric parameters, dimensions applied to geometric primitives, and geometric constraints; high-level semantic information includes feature definitions, design parameters, assembly constraints, material information, and custom metadata. The geometric topology information and high-level semantic information are integrated to form a set of data objects as the original feature data.
[0036] To better illustrate, the application programming interface (API), which is the official application programming interface provided by the source CAD system, automatically traverses the entire design history tree of the hull section model in a programmatic manner, and then identifies each modeling operation, such as "Pad", "Pocket", "Stiffener", "Hole", etc. The hull section model refers to the model unit in which the entire ship structure is divided into several blocks or modules according to regions or functions and constructed in the form of three-dimensional solids in the CAD system. It has complete structural features and design history and is the basic data unit in modern digital shipbuilding.
[0037] Specifically, for each identified feature, it encompasses both geometric topological information and high-level semantic information. That is, the feature not only records the type of ship product but also includes precise definition parameters. For example, for an extrusion pad, it includes the extrusion direction vector, extrusion depth, and the sketch object references it depends on. By deeply analyzing the sketch, all geometric primitives that make up the sketch, such as lines, arcs, and splines, are extracted, along with their precise set parameters, such as endpoint coordinates, radius, and control points. Dimensions and geometric constraints such as parallelism, tangency, coincidence, and symmetry are applied to the geometric primitives. Then, when processing the assembly model, assembly constraints such as fit, coaxiality, distance, and angle between each part are also extracted. Finally, non-geometric metadata attached to the model, feature, or part, namely high-level semantic information, such as part name, material grade, professional system (e.g., "ballast water system"), weight, creator, and creation date, are comprehensively extracted. All extracted information is organized into a set of structured data objects in memory, that is, by integrating geometric topological information and high-level semantic information to form a set of data objects. This set of data objects serves as the original feature data, which completely preserves the original design intent and avoids information dimensionality reduction during the data exchange process.
[0038] Further, step S2 includes: Step S21: Obtain the semantic mapping engine containing the semantic mapping rule library, define the semantic mapping rules from source CAD system features to ontology concepts based on the semantic mapping rule library, and perform parameter mapping and constraint mapping in sequence.
[0039] To clarify, the core of the semantic mapping engine is a configurable semantic mapping rule base, which is stored in a common technical format. The semantic mapping rule base is essentially a structured mapping lookup table, usually stored in the form of XML (Extensible Markup Language), JSON (JavaScript Object Notation) files, or database tables. Internally, it is implemented through a "key-value pair" structure, that is, establishing an index association between the API feature identifiers (Key, such as CATIA:Stiffener) of the source CAD system and the standard concepts (Value, such as ontology:Stiffener) in the semantic ontology, so that the semantic mapping engine can dynamically identify features by looking up the table.
[0040] Specifically, the semantic mapping rule base defines the mapping from specific features of the source CAD system to ontology concepts in an extensible way, such as using XML or database tables. That is, it defines rules through semantic equivalence transformation. For example, one rule may be defined as: CATIA:Stiffener -> ontology:Stiffener (mapping the stiffener feature identifier in the source CAD system CATIA to the standard stiffener concept in the semantic ontology); another rule may be defined as: NX:Extrude(type=Boss) -> ontology:PadFeature, that is, mapping "software-specific implementation data" to "general engineering attributes". By stripping away the software-specific naming conventions through semantic mapping rules, the true engineering meaning of the data is restored.
[0041] Next, the semantic mapping rule base defines the mapping of feature parameters, that is, parameter mapping. For example, the SectionName parameter of CATIA:Stiffener is mapped to the hasProfile property of the ontology Stiffener; the plane object referenced by its Limit.Plane parameter is mapped to the value of the hasEndPlane property. Here, SectionName is the field name of the profile specification stored internally by CATIA software, representing the software implementation level; while hasProfile is the standard term for defining profile section attributes in the semantic ontology, representing the engineering semantic level.
[0042] Then, constraint mapping is performed, mapping assembly constraint objects in CATIA, such as Constraint.Coincidence, to object properties defined in the semantic ontology, such as isCoincidentWith.
[0043] Step S22: Process the original feature data based on the semantic mapping rule base after the mapping is completed, instantiate the ontology concept, fill in the corresponding attributes, and convert it into an intermediate data file.
[0044] Specifically, the semantic mapping engine loads the semantic mapping rule base after mapping, automatically processes the original feature data, and instantiates the ontology concept according to the rules defined in the aforementioned step S21, fills in its attributes, and generates an intermediate data file that follows the ontology structure definition, which fully preserves the logical consistency and structural norms in the semantic mapping process.
[0045] Furthermore, the intermediate data file adopts either XML or JSON format, serving as a neutral carrier for information exchange independent of the source CAD system. Specifically, the intermediate data file preferably uses XML or JSON format, which has a clear structure and high readability. Both formats are widely used lightweight data exchange formats, capable of effectively describing complex data structures, and are easy for both humans and machines to read and parse. Completely independent of any CAD system, it acts as a neutral carrier for information exchange, ensuring compatibility and operability in cross-platform and cross-system environments, and avoiding integration barriers caused by proprietary formats of specific CAD systems.
[0046] Understandably, the target CAD system refers to the CAD system corresponding to the task requirements, such as AVEVA Marine (AVEVA Marine Design and Engineering) or Tribon M3 (Tribon Marine Information Model). When another engineer needs to open the hull section model in the target CAD system, the hull section model has already been parsed, extracted, and mapped, and exists as an intermediate data file, which is a logical model that carries the complete design intent of the source CAD system.
[0047] Furthermore, step S3 includes: Step S31: Use the target CAD system to parse the intermediate data file and deserialize it into an object model in the target CAD system's memory, and the object model has the same structure as the source CAD system.
[0048] Specifically, the intermediate data file is read by the target CAD system through a standard XML or JSON parser, and its contents are deserialized into an object model in the target CAD system's memory. The structure of this object model is consistent with the structure of the semantic ontology, that is, the object model is consistent with the structure of the source CAD system, which ensures the accuracy and integrity of the data during the cross-system conversion process.
[0049] Step S32: Perform reverse mapping and command generation based on the target CAD system, and clarify the feature dependencies and construction order of intermediate data file records.
[0050] Furthermore, in step S32, specifically: Pre-defined reverse semantic mapping rules are used to translate ontology concepts into application programming interface (API) call sequences of the target CAD system. Based on the API call sequences, the corresponding information stored in the intermediate data files is obtained to determine feature dependencies and construction order.
[0051] Specifically, reverse mapping rules are configured for the target CAD system to translate ontology concepts into API call sequences of the target CAD system. Here, API functions refer to the standard interfaces provided by the target CAD system software vendor. In practical applications, based on ontology concepts such as Stiffener in the intermediate data file, the semantic mapping rule library is dynamically searched, and the corresponding API functions in the target CAD system are automatically selected and called; that is, reverse mapping and command generation are performed. For example, when an ontology:Stiffener instance is parsed, the target CAD system looks up its hasProfile attribute value, such as L100x10, and finds the corresponding profile specification in AVEVA Marine's profile library. Then, the API function for creating the profile is called, and the path curves, start points, end points, and other information stored in the intermediate data file are used to complete the creation, so as to clarify the feature dependencies and construction order recorded in the intermediate data file.
[0052] Step S33: Following the feature dependencies and construction order recorded in the intermediate data file, reconstruct a local 3D model in the target CAD system that is equivalent to the source CAD system.
[0053] Specifically, feature tree reconstruction is performed. During the reconstruction process, the feature dependencies and construction order recorded in the intermediate data files are strictly followed to ensure that the feature tree structure generated in the target CAD system is consistent with that of the source CAD system. For example, the HullPlate entity must be created first before the Stiffener entity associated with it can be created through the isWeldedTo relationship. Finally, a brand-new, parameter-editable, semantically equivalent local 3D model is generated in the target CAD system. Based on this local 3D model, users can modify and parameterize it just like they would the source CAD system.
[0054] Understandably, to ensure conversion quality, after the local 3D model is reconstructed, a data verification module is activated to perform multi-level data consistency verification. The verification process is a multi-level comprehensive novelty check to compare the source CAD system, or its extracted original feature data, with the reconstructed local 3D model in the target CAD system.
[0055] Furthermore, in step S4, specifically: Based on the local 3D model, geometric verification, semantic verification, and structural verification are performed sequentially to generate verification results. The verification results are then generated into a report and fed back to the user, thus completing data interoperability.
[0056] Specifically, the process begins with geometric verification, which involves calculating key geometric quantities such as total volume, total surface area, center of gravity coordinates, and moment of inertia for both the source and target CAD systems via API, and comparing their differences to ensure they are within preset tolerances (e.g., volume difference less than 0.01%). Next, semantic verification is performed, comparing the semantic information of the two CAD systems to ensure that the values of any semantic information, such as the total number of parts, the number of specific features like valves, and key design parameters like hull plate thickness, are completely consistent. Finally, structural verification is conducted, comparing the number of nodes, hierarchy depth, and parent-child relationships in the feature trees or assembly structure trees of the two CAD systems to check for topological consistency. By integrating geometric, semantic, and structural verifications, a comprehensive verification report is generated, highlighting any inconsistencies for user confirmation or necessary adjustments, thus forming a complete quality control loop.
[0057] It can be explained that by accurately mapping the feature-level data of the source CAD system, i.e., the original feature data, to a unified semantic ontology of ship products, a semantically complete and unambiguous high-quality initial state is provided for the subsequent local 3D model reconstruction in the target CAD system. Unlike traditional geometric transformation methods, the ship data semantic interoperability method for heterogeneous CAD integration provided by this invention retains design parameters, assembly constraints, and engineering attributes, ensuring that the subsequent API-based automated reconstruction can accurately reproduce the original design intent, avoiding model degradation or reconstruction failure due to information loss. Furthermore, through a semantic-based transformation method, a good initial pose and complete engineering definition are provided for the subsequent model reconstruction, ensuring high fidelity in the interoperability process, and ultimately transferring the complete information contained in the source CAD system to the target CAD system without loss.
[0058] Understandably, by integrating the semantic ontology of ship products with the original feature data, that is, by delving into the feature level of the CAD model and using the semantic ontology as a bridge, the design intent is fully preserved, so that the reconstructed model has complete engineering semantics in the target CAD system and can be directly edited, which greatly enhances the reuse value of the design data. By providing a scalable and universal data exchange framework independent of specific CAD vendors, it effectively breaks down information silos caused by software heterogeneity, enabling seamless data flow throughout the entire ship lifecycle. Furthermore, it replaces the traditional, inefficient, and error-prone manual model reconstruction work with an automated data conversion process, significantly improving collaboration efficiency and reducing R&D costs. Specifically, it directly extracts raw feature data by calling the application programming interface of the source CAD system. This deterministic data acquisition method fundamentally eliminates the ambiguity and uncertainty inherent in feature recognition technology, ensuring high semantic accuracy. Simultaneously, the scalable and universal data exchange framework, namely the ship product semantic ontology and semantic mapping rules, addresses the limitation of coverage. It decouples the data extraction and data reconstruction processes. When faced with new or complex ship design features, it only requires defining new concepts and configuring corresponding mapping rules in the ontology to support them, without needing to reconstruct the system. This allows it to broadly cover various heterogeneous CAD systems and complex engineering semantic scenarios. Furthermore, the intermediate data files generated based on the semantic ontology of ship products and the original feature data, namely the high-fidelity model data rich in complete semantics, have laid a solid foundation for building a "digital twin" for the shipbuilding industry. This has strongly supported advanced application scenarios such as virtual assembly, performance simulation, and intelligent manufacturing, and promoted the digital and intelligent transformation of the shipbuilding industry.
[0059] This invention employs a three-stage method of "semantic parsing-mapping transformation-semantic reconstruction." The preliminary steps lay a solid foundation for the subsequent steps. Based on the semantic ontology of ship products, it fully utilizes domain expert knowledge. The deep integration and invocation of APIs in the source CAD system embodies software engineering technology. Formal logic is used in the application of the semantic mapping rule engine. This achieves lossless, intelligent, and bidirectional interoperability of ship model data in heterogeneous CAD environments, meeting the stringent requirements of modern ship collaborative design and digital manufacturing for data consistency and integrity. This ensures the design quality and engineering reliability of ship products, providing technical support for enhancing the core competitiveness of my country's shipbuilding industry.
[0060] A second embodiment of the present invention provides an electronic device, which includes a processor, a communication interface, a memory, and a communication bus. The processor, the communication interface, and the memory communicate with each other through the communication bus. The processor calls logical instructions in the memory to execute a semantic interoperability method for ship data for heterogeneous CAD integration as described in any embodiment of the present invention.
[0061] When it is in operation, it needs to use a semantic interoperability method for ship data that is oriented towards heterogeneous CAD integration. Therefore, whether the equipment and program data are integrated or different hardware is configured to produce functions with similar effects to those achieved by this invention, they all fall within the protection scope of this invention. This equipment has the same beneficial effects as the aforementioned semantic interoperability method for ship data that is oriented towards heterogeneous CAD integration, and will not be elaborated here.
[0062] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0063] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
Claims
1. A method for semantic interoperability of ship data for heterogeneous CAD integration, characterized in that, The method includes: Construct a semantic ontology for ship products; and obtain a source CAD system containing hull segment models, and extract raw feature data by calling the application programming interface of the source CAD system based on the hull segment models; Based on the semantic ontology of ship products, semantic mapping rules are established from the features of the source CAD system to the ontology concepts. The original feature data is then converted into intermediate data files through the semantic mapping rules. The target CAD system is acquired, intermediate data files are parsed, and a local 3D model equivalent to the source CAD system is reconstructed in the target CAD system. Perform multi-level consistency checks on the local 3D model to achieve data interoperability.
2. The method for semantic interoperability of ship data for heterogeneous CAD integration according to claim 1, characterized in that, Constructing a semantic ontology for ship products includes: Collect knowledge in the shipbuilding field and extract descriptions of core design concepts, terminology, classification systems, design rules, and constraints for ship products; Based on the description, define the top-level concepts and subclass levels sequentially to build the model, and define the corresponding data attributes and object attributes based on the top-level concepts and / or subclass levels to construct the domain knowledge base.
3. The method for semantic interoperability of ship data for heterogeneous CAD integration according to claim 2, characterized in that, The data attributes are used to describe the parameters of the ship products; the object attributes are used to describe the relationships between the ship products.
4. The method for semantic interoperability of ship data for heterogeneous CAD integration according to claim 1, characterized in that, The raw feature data is extracted by calling the application programming interface of the source CAD system based on the hull section model. Specifically: The application programming interface of the source CAD system is called to traverse the design history tree corresponding to the hull section model and extract geometric topology information and high-level semantic information. The geometric topology information includes geometric primitives, geometric parameters, dimensions applied to geometric primitives, and geometric constraints. The high-level semantic information includes feature definitions, design parameters, assembly constraints, material information, and custom metadata. The geometric topology information and high-level semantic information are integrated to form a set of data objects as the original feature data.
5. A method for semantic interoperability of ship data for heterogeneous CAD integration according to claim 1, characterized in that, Based on the semantic ontology of ship products, semantic mapping rules are established from the features of the source CAD system to the ontology concepts. These semantic mapping rules are then used to convert the original feature data into intermediate data files, including: Obtain a semantic mapping engine containing a semantic mapping rule base, define semantic mapping rules from source CAD system features to ontology concepts based on the semantic mapping rule base, and perform parameter mapping and constraint mapping in sequence; Based on the semantic mapping rule base after the mapping is completed, the original feature data is processed, ontology concepts are instantiated, corresponding attributes are populated, and the data is converted into intermediate data files.
6. A method for semantic interoperability of ship data for heterogeneous CAD integration according to claim 5, characterized in that, The intermediate data file adopts either XML or JSON format and is a neutral carrier for information exchange, independent of the source CAD system.
7. A method for semantic interoperability of ship data for heterogeneous CAD integration according to claim 1, characterized in that, Parse the intermediate data files and reconstruct a local 3D model equivalent to the source CAD system in the target CAD system, including: The intermediate data file is parsed by the target CAD system and deserialized into an object model in the memory of the target CAD system, and the object model has the same structure as the source CAD system. Based on the target CAD system, reverse mapping and command generation are performed to clarify the feature dependencies and construction order of intermediate data file records; By following the feature dependencies and construction order recorded in the intermediate data files, a local 3D model equivalent to the source CAD system is reconstructed in the target CAD system.
8. A method for semantic interoperability of ship data for heterogeneous CAD integration according to claim 7, characterized in that, Based on the target CAD system, reverse mapping and command generation are performed to clarify the feature dependencies and construction order of intermediate data file records, specifically: Pre-defined reverse semantic mapping rules are used to translate ontology concepts into application programming interface (API) call sequences of the target CAD system. Based on the API call sequences, the corresponding information stored in the intermediate data files is obtained to determine feature dependencies and construction order.
9. A method for semantic interoperability of ship data for heterogeneous CAD integration according to claim 1, characterized in that, Perform multi-level consistency checks on the local 3D model to achieve data interoperability, specifically: Based on the local 3D model, geometric verification, semantic verification, and structural verification are performed sequentially to generate verification results. The verification results are then generated into a report and fed back to the user, thus completing data interoperability.
10. An electronic device, characterized in that, The device includes a processor, a communication interface, a memory, and a communication bus. The processor, the communication interface, and the memory communicate with each other through the communication bus. The processor calls logical instructions in the memory to execute the semantic interoperability method for ship data for heterogeneous CAD integration as described in any one of claims 1 to 9.