Integration of EMU Overall Design Model Based on Ontology–Knowledge Collaboration
Source abstract
Abstract
The whole train design of an Electric Multiple Unit (EMU) involves multiple domains and scenarios, thus requiring comprehensive consideration of various factors during the design process. Traditional design methods often utilize text-based approaches to model systems; however, such documentation-based designs often suffer from semantic heterogeneity, inconsistent data sources, and also struggle to provide a more intuitive overview of the overall design process. To address these issues, this paper proposes a method based on ontology–knowledge collaborative drive to achieve integration of the overall EMU design. Firstly, we employ the System Modeling Language (SysML) to construct the Model-Based Systems Engineering (MBSE) model of the EMU, establishing functional and physical architecture element models, with the EMU MBSE model serving as input. Subsequently, in the requirement model, architecture model, and traceability model, we utilize top-level ontology to construct the EMU ontology framework in a top-down manner. Lastly, leveraging the Neo4j database, we employ a knowledge graph (KG) approach to fill domain knowledge into each model in a bottom-up manner, thereby realizing the ontology–knowledge collaborative drive for the overall EMU design construction. The effectiveness of the proposed method is validated using the EMU Passenger Information System (PIS) and Traction transformer System (TS) as examples.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Semantic Web and Ontologies · Service-Oriented Architecture and Web Services · Business Process Modeling and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Automobile and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China
Funding
Tianjin Municipal Education Commission Research Program Grant · Tianjin University of Technology and Education Research Initiation Grant
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